Numerical simulation of PEP cases and cloud seeding experiments

Report 83-4
HtM:RICAL SIMUlATION OF PEl' CASES ANI>
CLOUD SEWING EXPERIHUiS
8y: H. D. Orville, J. H. Hirsch,
and R. D. Farley
Prepared for:
Weather Modification ProgrUllle
WOrld Meteorological Organization
Case postale No. 5
01-1211 Geneva 20, Switzerland
Nov_er 1983
Purchase Order No. 29462
.>
Institute of Atmospheric Sciences
South Dakota SCh~l of Mines and Techn<>logr
Rapid Citr',.:South Dakota 57701
Report 83-4
NtHRICAL SIMUlATION OF PEP CASES AND
CLOOD SEEDING EXPER~i'S
By: H. D. Orville, J. H. Hirsch,
and R. D. Farley
Prepared for:
Weather Modification Progr8Jlllle
World MeteorologicaI Organization
Case postale No.5
01-1211 Geneva 20, Switzerland
Novellber 1983
Purchase Order No. 29462
Institute of Atmospheric Sciences
South Dakota School of Mines and Technology
Rapid City, South Dakota 57701
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Sd.c'e ~tl.. pU1 1. tun C1uU) tb .If<<c,.. or cloud
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TABU OF CONTEN'IS
PIlHACI: ••••••••
LIST OF FIQJRl'S •••
LIST OF TABLES • • •
iii
vii
ix
1. Il\'TRODUCTION • •
2. foI)['EL DESCRIPTION • • • • • • • • • • • • • • • • • • • •
2.1 C-eneral Aspects • • • • • • • • • • • • • • • • •
2.2 Cloud Microphysics •••••••••••••••
2.2.1 Bulk "ater parmeterhation • • • • • • •
7.2.2 Water conservation equations •••••••
2.3 Seeding Sia:ulations •••••
7.3.1 Dry ice seeding •••
2.3.1.1 I:quations.............. 9
2.3.1. 2 Time-step considerntions •••••. 12
2.3.2 Silver iodide seeding • • • • • • • • • • • 13
3. FIELD OBSERVATIONS AND CLOUD )«)[lEL RESULTS. 19 FEBRUARY
1980 CASE • • • • • • • • • • • • • • • • • • • • • • •• 16
3.1 Observations • • • • • • • • • • • • • • • • • • •• 16
~.2 Hodel Results - Unseeded Cloud ••••••••••• 16
~.3 Dry Ice Seeding Si~lations • • • • • • • • • • • •• 19
3.3.1 VALICI case • • • • • • • • • • • • • •• 21
3.3.2 VALle2 case •• • • • • • • • • • • • • • • 21
3.3.3 VALIC3 case •• • • • • • • • • • • • • 24
~.4 S11ver Iodide Seeding Simulations. • • • • • • • • 24
3.4.1 VALlA2 case • • • • • • • • • • • • • 24
3.4.2 VALIA3 case • • • • • • • • • • • • • 28
3.4.3 VALlA4 and VALlAS cases ••••••• 28
3.4.4 VALIA6 case •• •••••••••• 28
3.5 Discussion •••••• • • • • • • • • • • • • • •• 31
vi
TABU OF CON'IENTS (Cont.)
4. FIELD OBSERVATIOOS AND CLOUD J«)()EL RESULTS. 14 MAY 1981
CASE • • • • • • • • • • • • • • • • • • • • • • • • • •• 34
".1 Introduc.tory Remarks •••••••••••••••• 34
4.2 Observations •••••• • • • • • • • • • • • • •• 34
4.3 Model Results ~ Unseeded Cloud (0700Z Sounding) • •• 34
4.4 Model Results· Seeded Cloud (C7aOZ Sounding) • • •• 42
4.S Seeding Potential. • • • • • • • • • • • • • • • •• 42
4.5.1 Method. • • • • • • • • • • • • • • • • • •• 42
4.5.2 Aircraft anaylsis analog. • • • • • • • • •• 49
4.5.3 Radar analysis analog ••••• • • • • • •• 51
4.5.4 Discussion. • • • • • • • • • • • • • • • •• 52
4.6 Nodel Results· Unseeded Cloud UOOZ Sounding. • •• 52
4.7 Discussion •••••••••• • • • • • • • • • 62
S. SlttfARy •• • • • • • • • • • • • • • • • • • • • • • • 64
ACKNQlrrlLE:DQoIE.NT ••••••••••••••
REFERENCES ••••••••••••••••
.5
.6
vii
LIST OF FIGURES
Cloud physics processes sinulated in the model ••
"'.ass weighted .ean terllinal fall velocities of
rain. snol<i', and hail as a function of air density
Skew-T plot of 19 February 1980 sounding taken at
Villanubill. Spain. at 1100 Qn' • • • • • • • • • 17
The natural sblUlation VALIN2 at 30. 60. and
90lllin • • • • • • • • • • • • • • • • • • • • • 18
The no-seed simulation VALlNS at 30. 60, and
90 min • • • • • • • • • • • • • • • • • • • • • 20
Cloud ice and snow content field comparisons
between the no-seed siallation VALINS and the seed
silllUlation VALIC2 at IS Jdn • • • • • • • • • • •• 22
Cloud ice and snow content field COllparisons
between the nOo-seed siD.llation VALINS and the seed
siwlation VALle2 at 24 min • • • • • • • • • • • • 23
Cloud iee and snow content field comparisons
between the no-seed simulation VALINS and the seed
simulation VALICt at 30 min •• • • • • • • • • • 2S
Rain accUP1llation at the ground along the x·axis
at 48 Illin •• • • • • • • • • • • • • • • • • 26
10
II
J2
13 ...
The AgI seed si1ll.l1ation VALIA2 at 39. 60. and
90 Din ••••••••••••••••••••
The AgI seed si1m.llation VAL1A3 at 45. 60. and
90 Din •••••••••••••••••••••••
The AgI seed siblUlation VALLA6 at 43. 60. and
90 min •••••••••••••••••••••••
Skew-T plot 14 May 1981 taken at Villanubla.
Spain •••••••••••••••••••••••
The no--seed siJiulation VAL2NS at 63. 75. and
81 llin ••••••••••••••••••.••••
27
2.
3S
36
viii
LIST OF FIGURES (Cont.)
Nl.Sber !!!!!. !!J!
Ub The no-seed sbtulation VAL2NS at 87. 93. and
99 .1.n • • • . • • • • • • • • • • • • • • • • • • • 37
IS The cloud nter field of VAL2NS at 75, 81, 87. and
93 min • • • • • • • • • • • • • • • • • • • • • •• 38
16 The snow content field of VALlNS at 75, 81, 87, and
93 min • • • • • • • • • • • • • • • • • • • • • • • 3~
17 The hail content. field of VAUNS at 81. 87, and
93 min • • • • • • • • • • • • • • • • • • • • • •• 40
18 The rain content field of VALZHS at 81, 87. and
93 min • • • • • • • • • • • • • • • • • • • • • •• 41
198 The CO2 seed siltlUlation VAL2Cl at 75, 81, and
87 atn • • • • • • • • • • • • • • • • • • • • • • • 43
19b The CO2 seed sbrulation VAL2el at. 93 and 99 Jlin •• 44
20 The cloud water field of VALle} at 75, 81, 87. and
93.1n • • • • • • • • • • • • • • • • • • • • • •• 4S
21 The snow content field of V,\L1CI at 15, 81, 87, and
93 llin • • • • • • • • • • • • • • • • • • • • • •• 46
22 The hail content field of VAL2Cl at 75, 81, 87, and
93 llin • • • • • • • • • • • • • • • • • • • • • •• 47
23 The rain content field of VAL2Cl at 75, 81, 87, and
93 IIin • • • • • • • • • • • • • • • • • • • • • • • 48
24a The natural simulation of VAL3N2 at 30, 36, 42, and
48 IDin • • • • • • • • • • • • • • • • • • • • • • • 54
24b The natural simulation of VAL3N2 at 54, 50, and
66 min • • • • • • • • • • • • • • • • • • • • • • • 55
25a The cloud water field of VAL3N2 at 30, 36, 42, and
48 Din • • • • • • • • • • • • • • • • • • • • • • • 56
25b The cloud water field of VAL3N2 at 54, 60, and
66 min • • • • • • • • • • • • • • • • • • • • • • • 57
r
ix
LIST OF FIGlJRf.S (Cont.)
Number !!.!.!=. !!I!
268 1he snow content field of VAL3N2 at 36, 42, and
48 IJlin • • • • • • • • • • • • • • • • • • • • • 58
26b The snow content field of VAL3N2 at 54, 60, and
66 min. • • • • • • • • • • • • • • • • • • • • S9
27 The graupel/haU content field of VAL3N2 at 54. 60,
and 66 JIlin • • • • • • • • • • • • • • • • • • • 60
28 Nodel output of snow, graupel/haU. and cloud
liquid water contents along a constant height
corresponding to the aircraft saIlpl1ng level • • 61
29 Sample of Wy_ng Queen Air aircraft data for
14 May 1981 •••••••••••••••••••• 63
LIS1' OF TABUS
Key to Figure 1 •
Precipitation results - stratU!l clouds. • • • • • • 32
S\Jll!fIlAry of results. • • • • • • • • • • • • • • •• S3
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1. INTRODUt:TION
Cloud moul"ls range in J:i:!.('- UIH.! cCltllplexity fr(\m 1.ero-dimensionlll,
stNloy-stllte ones (pllrcel mooels) to three-JimensiOllUI. tim()~uepcnd(lnt
(30T) mouels. Very conplex microllhysic$ can be treoted in the simple
dynamic models, but only highly parameterhed microphysics in the 301'
cloud models due to computer limitations. Intermediate to these models
are the two-diDlensional, time-dependent (2OT) ones which offer the
possibility of performing cloud seeding simulations with moderate
microphysical cOrrq>lexity and more realistic air flows than the one­dimensional
models. These 20T cloud model solutions involve considera­tion
of cloud cell interactions and microphysical/dynamical interactions
on domain scales of a few 10'5 of kilometers (using 100 m to 200 m grid
intervals) and over time spans of a few hours (time steps of a few
seconds). Even so, some compromises with the microphysics have to be
made to allow many operational runs of the models and a significant
nUJl1ber of cases to be tested.
The 20T cloud model results reported on here use simplified
procedures for the microphysics as well as simpler 2-D dynamics. The
treatment of the precipitating particles relies on the bulk water
technique, ,",'hich essentially assumes that the precipitating water or
ict' content is distributed in drops or ice particles that fit an
inverse exponential size distribution, albeit a different one for
each type of precipitating content considered. This maKes impossible
the consideration of the many shapes, crystal habits, and variable
densities characteristic of snow, graupel, and hail. Rain and snow
are treated in separate equations. The graupel and hail field are
considered as one and are treated in one equation. Small hail con­tents
«1.0 g kg-I) are dominated by graupel and the mass weighted
mean size (0 = 3.67/"G) for larger contents is rarely larger than
several millimeters. By convention, hail has a diwneter of 5 lIlJlI or
more, but we refer to all graupel, ice pellets, frozen rain, or hail~
stones as ''hail'' in the hail content field. Further details of the
method Bre given below.
In the sections to follow, a description of the cloud model and
the seeding: technique is given followed by sections concerned wi th
the natural cloud model results and comparison with observations,
the C02 and AgI seeded cloud results, and a general discussion
and conclusions.
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2. NOOn DESCIU PTION
2.1 General Aspects
The cloud model is two-diJllensional, ti'lle·dependent with bulk water
microphysics. The dOlllain of the model is 19.2 h in both the X and Z
dimensions with a 200 m grid interval. AtlJlOspheric wind, potential
telllperature, water vapor, cloud liquid, cloud ice, rain, snow and
graupel/hail (in the fono. of ice pellets, fro ten rain, graupel, and
SJDall hail) are the main dependent variables. The model has been
developed fro. the "·orks of Orville (1965), Liu and Orville (1969),
"isner et a1. (1972), Orville and Kopp (1977), and Lin et a1. (1983).
Extension OTthe node1 to sillUlate deep convection has bee'Ji'"Ude using
a density weighted streaJll function (Olen and Orville, 1980). The non·
linear partial differential equations constituting the llOdel include
the first and third equations of motion, a thermodynuic equaticn,
and water conservation equations (for its three phases).
The llOdel has been designed such that aesoscale convergence can
be superiJZlposed in the lower levels and divergence in the upper levels,
,.-hlch can result in stratus.type clouds being forced under certain
atlllOspheric conditions (Oten and Orville, 1980). The DOdd is there.
fore capable of silllUlating the stratus or nimbostratus.type clouds
found to be typical of cold late winter or early spring. conditions in
the Spanish project. The 1Il0dei has also been developed to include a
seeding agent, either dry ice or an ice nucleant such as silver iodide.
These are described, respectively, in Kepp et a1. (1983) and Hsie et
~ (1980) and outlined below. - - -
The production of cloud water, cloud ice, rain, snow, and
precipitating ice are sh:ulated using the bulk water techniques. The
production of rain from cloud water is simulated using equations based
on the work of Kessler (1969) and Berry (1968). Graupel/hail is formed
by freeting rain to ice by means of an equation due to Bigg (1953), or
by aggregation of snow or capture of snow or cloud ice by raindrops.
An approxiJlltltion to the Bergeron.Findehen process is used to trans­fOn!
scme of the cloud water into snow. Growth of hail is governed by
equations for vet and dry growth ()!usil, 1970). Cloud water lIIay be
transfo~ to clOlld ice in the region between O·C and -40·C using an
equation developed by saunders (1957). HOIIIogeneous freeting takes
place at the -40·C level. Rain, snow, and graupel/hail possess
appreciable terminal £011 velocities. Cloud water and cloud ice
have tero te:minal velocities and thus travel with the air parcels.
Evaporation of all fol'P.5 of hydrometeors and melting of snow and
graupel/hail are also siJlulated. Figure I and Table I show the
cloud microphysical processes sinllated.
~
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WATER VAPOR
CLOUD
ICE
~; Cloud physics processes silllUlated in the Model.
1'Or&i\ explanation of the sYlllbols.
see Table 1
hy to F1l:llr~ I
Heltlq:of<l...... l«tof_Clou<l ..nn.T~YO·
Dq>osltJonal Crowtll of cloud Ice U ~'"Pe1l,eoCclOd<l.Ucr.
Il0..0Eeneou,s hudnj: of clO<l<l"eter to fonoc1oud ice.
,\ctret1on of raln by cloud Ice; produces ,nOlI 0.. Sra"'Pe1 dependlq: on the UIOUIIt
of ..dn.
AcCTetlonofcloudlclOby ...in;prod~.. s_orJTOq>ddepudJ..... onUla_t
of ..au.. .
Aco:«UonoCcloud"aterbrnin.
Eupor.tionofuln.
AccreUon of,1IO'Ii by rdn: produce' Itlupel Hnlno.. snOllexceed.thra,hold
andY·Yo •
Accretion of c1oud ..t ... by s""". proclucu ... trT' TO or ...b lfY ~ TO'
Aho eM.on~••_ -eltlflJ lor .T ~ YO'
nereUoe of raiA by ._. For T • TO' proct..::es rnupel If ...iII Or s_ eKeeds
~~:::~d; if not, produces 5_. For T !. To' tu 'CCrlrted "ater ellll.a..cu ._
Acc..etlonofcloudlc~by&_,
Autoconversion (a.uresatlon) of cloud lco to fOTll.now •
....lleronptoeen(deposltlonllJld ..l.aUs)-transferofcloud"aurtofor.'_.
MeH1nl of snOll to fOnl ..dn, T~TO'
AutOC(lnver,lon (auregstion) ofsn""to/OTllcra",.1.
.........bllbtlc frecdllZof ...lnto f.... CI"aUJ'I01.
Accretlonofcloud"atnb)'ITaur-1.
Accretlon of cloud lee by 1T.upe1.
Accretlonofra1nbY/lraup.l.
Accretion of SnOW bY/lraupel.
Subli..U<lRoflra",el.
MeltJnC <If IT''''Pel to f<lno rain, T ~ TO' (In tIlh ..ql-e. 'CH:Jl h IlSs.-d to
bt shed as ra1Jl.)
~;;:~h~~h~ri:l~/:;';~ctlifc:":s'~P':~:'~~~"t: ~W't:r
2.2 Cloud Microphysics
2.2.1 Bulk water pnGleted:ation
Exponent.ial she distributions aTe hypotheshed for the
precipitation particles:
where noR. noS. and naG are the intercept parameters of the rain. snow,
and hail size distributions, respectively. The noR is given by Marshall.
Palmer (1948) as 8 x 10.2 cm.. li • According to the measurements of Gunn
and Marshall (1958), nOS is given as 3 x 10·2. em-Ii. Observations by
:~~e~ ~o~:I:~!eio;I:~ o~R~a~~. d;~~r~~u:;~n~i~::e~~ ~fv~~~e r~in.
snow, and hail particles, respectively. The slope parameters of the
rain. snow. and hail she distributions. AR' AS. and ),G. respectively.
are detel'lllined by multiplying (2·1), (2-2), and (2-3) by particle mass
and integrating over all dilUlleters and equating the resulting quantities
to the appropriate water contents; they may be written as
(2·4)
(2-5)
(2-')
The tendnal velocities for a precipitating particle of diameter
Oa. Os. and I\; are:
(2-1)
(2-8)
(2-9)
The terminal velocity of rain, VOR' is suggested by Liu and Orville
~~:9il~~~)~er~:~n:t;=:tas~~r:as~:a~i~~sC:i-~la~nd~~::r~:spec_
tively. The tel'1Dinal velocity of SJlO'l, Uos, is based on the relations
suggested by Locatelli and Hobbs (1974). Specifically, Uos is that
appropriate for graupel-like snow of hexagonal type, with the constants
c and d being 152.93 cm1- d s~l and 0.25, respectively. The square
root factor involving air density allows for increasing fall speeds
with increasing altitude, similar to Foote and du Toit (1969). The
tendnal velocity of hail, lIDc, is proposed by Wisner et al. (1972).
with the drag coefficient, CD, asSUllled to be 0.6. --
As in Srivastava (1967), the Jlass-weighted aean tendnal velocities
are given by:
(2-10)
where Uo is the tendnal velocity of a precipitating particle of diameter
0, 1(0) is the JIbing ratio of a precipitating particle of dialleter 0,
and 1 is the mixing ratio of a precipitating field. The application
of (2-10) to each precipitating field produces the 1Il8Ss~weighted JIlean
terminal velocities of rain, snow, and hail.
v = ar(4+b) r~..2.)~
R ~P
The nlass weighted llIean terminal velocities of rain, snow, and hail are
shown in Fig. 2.
SNO~ _
---=-~_.-::::-: -'7:::::'::.-::::.-::::~:
';":':':::::::::::
--
16 HAIL ---
-- //,_.... --RA~_
/
/
// / .
1/ ·····
i/....·
_.- _.-"
---
~: Mass weigh~ed lIean teminal fall velocities of rain. snow, and
JliIl"iS a func.tion of air density.
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2.2.2 Water conservation equations
Five conservation equations are considered in this model. one for
each water substance and another for the seeding agent.
(2-14)
(2-15)
(2-16)
(2-17)
(2-18)
where q '" tcw + t Cl + r; t cw ' tCl' t R• t S' tC' r. and Xs are the mb.:ing
ratios for cloud water. cloud ice. rain. snow. hail. water vapor. and a
seeding agent. respectively. The s)'1llbols PRo Ps • and Pc repres~nt the
production teI1l1s for rain, snow. and hail, while S+ and ·S~ represent
source and sink tenr.s for the seeding agent. For a detailed explana~
tion of the derivations of these terms. the reader is referred to
Wisner!!..!h (1972). Hsie !!..!.h (1980). and Lin!!!.!.:. (1983).
The last term in (2.15). (2~16). and (2~17) are the fallout terms.
All of the first terms on the right~hand side are advection terms; the
second terms are diffusion terms. For details on the dynamic equations.
the reader is referred to Chen and Orville (1980). Next. the techniques
for simulating cloud seeding are described.
2.3 Seeding Simulations
2.3.1 Dry ice seeding
2.3.1.1 &luati0118. In many field experiments. dry ice pellets
are released at cloud top and fall through the cloud. leaving a trail
of ice crystals behind. To siJDulate this in the model. a field of CO2
is initialized with a few grid points containing C02 at the top of the
cloud. The CO2 then descends through the model cloud. subliming as
it falls.
10
The center point of the initial dry ice field is specified. The
aircraft dispensing the seeding agent can be as~ to travel in a
hor1z.ontal plane in the y.directlon (perpendicular to the plane of the
1DOdel). P8.TUIeters control the horizontal and vertical extent of the
initial dry ice. The core of the dry ice content is • constant value
and may be lilldted to as little as one grid point or ....y extend vertically
or horhontally over several grid points. Outside the COTe region of
the seeding field, the dry ice aixing ratio decays exponentially with
distance. At the first grid poInt outside the core, the value is 13.5'
of the core value; at the second grid poInt, loS'. lU'Id 0 beyond that.
Initially in these CO2 experimeTl.ts. the core of the dry ice is spread
over three vertical grid points and one horizontal plus the decay grid
points. With a core value of 6.11 x 10-10 g g-l for the CO2 mixing
ratio, this results in a total of about 90 g of C02 per km in the
y-direction of the model. initially. Once activated, the dry ice
field evolution is controlled by sublimation, the terminal velocity
of dry ice pellets, and advection.
The sublilll8tion rate for the dry ice is based on work done by
(Fukuta !!..!h., 1971) and l'Il3y be written as
d(C0
2
)
~ = 8.16 x 10-8 D!P (O.097T + 9.4P + 137.3)
• (0.097T + 9.4P - 25.4)
(2-19)
where T is in Kelvin, P is in atJlOspheres. and D is the diUleter of
the pellet in centilleters. Temperature and pressure are available in
the model. The dillllleter of the pellets is known initially but must be
estilll8ted as the dry ice sublimates. The symbol CO2 is the mixing
~:~~ot~: ~~:m:~ri~~.t~:ds~li~~~eP:~~:t~~ ~h:i~~~:lP:;;:t~f~~e~~;-
in the model domain Is determined at each time step. as well as the
amount which has fallen out of the grid, llnd these amounts are used
with the initial mass of dry ice to cOlDpute the diameter. The
equation is:
(2-20)
c
11
where Ms is the total mass of dry ice in the grid, MIS is the 1nitial
JlIllSS of dry ice dispensed in the grid, and MJ:s is the dry ice which
has fallen to the ground or which has been adveeted through a
boundary. The average diaJlleter of the initial pellets is 1.5 01.
This scheme for dctenrining the pellet she assUlIes that they are the
sase size everywhere in the grid. The terminal velocity of the pellets
is detenlined froll:
(2-21)
which is talen froll Fukut. et al, (1971). but has been adjusted to fit
experimental data (Holroyd !!..!h.. 1978).
Advection and fallout are the last physical effects which must be
accounted for. Thus the equation for the time rate of change of d1')'
ice at: a grid point is
(2-22)
where d(COzl/dt is the sublhl8tion rate froJlI (2-19). and the first and
second te:nllS are the advection and the fallout tem, respectively. The
sydlol Vis the wind vector and p is the air density. This is the
additional conservation equation needed to trace the 002 field,
replacing (2-18) above.
As the dr)' ice pellets faU through the clouds. they leave behind
a trail of ice crystals which are expected to grow quickly in the liquid
water saturated enviroTl!lent. Experimental data suggest (Fukut. et
Tkh;9~~e~~aih;~:1c~s~~~: ~~t:l~l:~1111O~~c~C:h::ed~ei~~S~;i~~.
traversed) whose mung ratio is determined by
(2-23)
where tCI is the cloud ice mixing ratio and mI is the mass of an ice
crystal. The mixing ratio of cloud ice depends on the rat.e of sublima.
tion of the mixing ratio of dry ice. Where the air temperature is
above freeting, no ice foms, but the dry ice continues to sublillle.
The source for the cloud ice formed by this initiation process is
supercooled cloud water.
12
. Cloud iee also fOr1D5 naturally froll an exponential equation by
fletcher (1962). whieh h8$ about one active ice crystal per liter at
.20·C. Natural ice rill fOB in both the unseeded and seeded cases.
In the 1DOdel, the CO2 does not interact in any other w.y with the cloud
physics. The cloud lce which is formed (whether by the dry ice or
naturally) grows by vapor deposition and interacts with cloud liquid by
riming until it reaches precipitation she (snow). Tht' snow interacts
with the cloud liquid and cloud ice to fon IIhail" (primarily graupel).
Hail can also fOB in the later cloud stages as rain collects snow and
cloud ice in sub-zero regions of the cloud. Thh rain content freens
instantaneously. Rain can form from the gelting of the ice particles
and/or the shedding of cloud liquid from hail. These cloud 1IIicnlphYSlcal
processes are described in Lin et al. (1983). Orville and Kopp (1977).
and Wisner!!.!!.:. (1972). --
Early tests ""i th the IIlOdel have indicated an increase in cloud ice
mass (and. consequently. the number of cloud ice particles) not commen­surate
with observations. Hence the maximum amount of cloud ice at a
grid point has been made a function of temperature. The Fletcher curve
for active nuclei is used.
NC = A exp[0.5{-Tc)] (2-24)
where NC is the number of active nuclei per grail of air (liter). A is
a constant dete:rmined frOlll observations in the cloud. if possible. and
Tc is Celsius telllperature. If no ice is observed. the default value
for A is 10- 5 per liter which is activated at -20·C and results in
about 0.2 ice c:rystals per I1ter at -20·C. The auiWl.ll!l cloud ice is
set equal to
(2-25)
where MSO is the gass of a 50 lim (equivalent liquid radius) particle.
If the cloud ice content exceeds this 8IIOUnt, the excess cloud ice is
converted to snow. A fraction of the cloud ice is usually converted
to snow each time step. Generally, the cloud ice will increase to SOlllC
arolUlt less than the maximum. and the rate of growth will I118tch the rate
of conversion to snow. Koenig's equations (Koenig, 1971) are used to
calculate the Tate of growth of the cloud ice, which is assumed to be
composed of 10 lim (equivalent water radius) crystals. At _40°C, the
cloud liquid remaining. if any, is completely fro ten to cloud ice.
2.3.1.2 TimB-8UP considerations. Cloud models which
simulate the drop of dry ice pellets and use a conservation equation
to solve for the dry ice mixing ratio must be used with care in running
seed and no-seed cases to see that the same sequence of time steps is
used in both 21185. OtheTWise, differences in results lIIay be due more
to a difference in the time step selection than to a difference caused
by the CO2 induced glaciation.
c
13
The basic reason for this fact is that dynamic cloud model results
are generally sensitive to the time-step, even though the Courant­Friedrichs-
LeW)' (CFL) linear stability condition is satisfied. Wiin­Nielsen
(1979) has presented evidence of the time-step sensitivity for
synoptic scale barotropic models. In his study, the phase speed and
amplitude of waves were more accurately depicted in model runs with a
time step considerably smaller than the CFL criterion would indicate.
Evidently the same sensiti.vity can exist in dynamic cloud models. Even
very small model differences may affect the accUlll.11ated precipitati~n at
the ground, which is a sensitive integrated effect over space and time.
The cloud seeding simulations in these PEP cases are done on weak
convective or stratified clouds, with observed tops to 5 or 6 km and
vertical velocities normally less than 10 m s~1. An unseeded model
run is Illade to reproduce the tyPical clouds observed on that day (more
than one run may be required). Fifteen~second time steps are used
initially, A seeding time is selected and the model rerun from that
time with a simulated release of dry ice pellets, represented as a
mixing ratio of CO2 , These pellets fall initiallY at 20 III s-1 or more,
and the time step in the model must be reduced (to 3.75 s) to keep the
conservation equation for CO2 numerically stable. The change in the
time step thus changes the results slightly, even if no dry ice pellets
were allowed to interact with the cloud processes.
To correct for this effect, an unseedcd model run is made with
the exact sequence of time steps as those used in the seeded model run.
Consequently, a minimum of three runs is needed to obtain comparable
unseeded and seeded model runs. Alternatively, all computer runs could
be made with a tiEe step at the start small enough to insure nwnerical
stability for flows of some arbitrarily large value, say 40 111 s-1 or
less.
2.3.2 Silver iodide seeding
The simulation of silver iodide seeding follo""$ Hsie et a1. (1980),
whose model did not include a snow content field. The major Cli'iinge to
their seeding DlOdeling is the imposition of an upper limit on cloud ice
content, beyond which excesses are· used to fonn sno",', as described
above. Because cloud ice particles in a supercooled cloud easily grow
to form snowflakes, this change makes the simulation more realistic.
Major assumptions are:
1. All the silver iodide (AgI) particles are asswned to be the
same size (radius - 0.1 lim) in calculating the collection rate.
2. The terminal velocity of silver iodide particles is asswned
small enough to be ignored.
3. One liquid drop is asswned to capture no more than one active
ice nucleus.
14
4. The collection rate of ice particles for silver iodide particles
is disregarded.
S. The lIui_ cloud ice content is Haited by a teJIperature
dependent function .s described above {in Eqs. (2-2') and (2-25)). The
ntmbeT of artificial nuclei to be added to the mmber of natural ice
nuclei to fOnl ice crystals is given by Blair!!.!!.:.. (1973).
Na =- 0 liter-I. Tc > -sC
= exp (-0.022 ~ - 0.88 Tc - 3,8) liter-I, -SC ~ Tc
~ -2oe (2-26)
.. 160 liter-I, ~2OC > T
c
The initial seeding pattern for silver iodide used for the results
reported below is composed of 11 core grid points in a horizontal or
vertical pattern with the exponential decrease in the surrounding grid
~;n~~~d;:~~~b~: ~~V~ff~~lih: ~~l ~s;ciJ '~i;i~~' ab~u~o~~o V:l~~ for
AgI per kilometer in the y-direction.
As. described in Hsie et a1. (1980). the silver iodide particles
interact with the cloud liqlii~rain. and water vapor fields to produce
ice crystals. Contact and deposition nucleation are siallated directly.
tdl.ile condensation-freezing nucleation effects are i1l{l11cit in the
generator nucleation curve for the activation of AgI particles (2-26).
The physical effects of inertial i1l:pact and Brownian collection are
modeled for contact nucleation. Most of the AsI particles work 35
deposition or condeMadon freedng nuclei in the IlOdel.
li'ith regard to the AsI activation. the modeled activation rates
have been found to be too high in the warner portions of the cloud
(-S·C to -20·C). particularly if the AgI particles rell8in in the war.
sectors of the cloud for long periods of time (private connunieations
with B. A. Silvennan). The problem relates to the continual activation
of the AgI particles $0 that (2-26). while properly representing the
;~~~~:~e:c~}V~~;O~~fp~~~i~;;:~;; ~:a~t~~ :~C~~:i::me~~=:r:~~~
[see Eq. (27) and prior discussions in Hsie et 81. (1l180)]. This
problem is less serious for strong updraft cloUdS than for weak up­draft
clouds because these more vigorous clouds will quicklY carry
the seeding agent into colder regions where, in any event, all of
the AgI particles ...·ould be activated.
The interpretation one should place on the AgI seeding effects on
the stratus-type clouds reported on below is to consider that JIlUch more
silver iodide than modeled would be required to provide the indicated
effect in a field experiment. Alternatively, the amount of CO2 required
to produce the equivalent number of ice crystals as the AgI could be
calculated, but even here problems arise because of the short time that
the C02 produces crystals in the cloud. So the combination of time of
fOTlll8tion and nwnber of ice crystals formed is difficult to produce the
same effect in both AgI and C02 seeding simulations. This is as yet an
unresolved problem in the modeling ot seeding effects in this cloud
model. Coordinated modeling and field efforts will be required to
sort out the many complexities. The cloud model seeding results to
follow are suggestive and not definitive.
15
16
3. FIELD OBSERVATIONS AND CLOUD MODEL RESULTS,
19 FEBRUARY 1980 CASE
3.1 Observations
The radiosonde sounding for this case is given in Fig. 3. The
marked stability and high moisture content in the lower layer lias
overlain by an unstable, dry level aloft. As described in PEP Report
No. 22, a cold low, developing from a lagging surface trough, deepened
west of Portugal and remained south of the project area for the period
18-20 February. On the 19th, the upper cloud layers thickened during
the morning hours. A NW-SE oriented rain band moved through the area
from SW to NE during midday. Cloud physics ain:raft flights reported
the core of the band to be completely glaciated and precipitating,
while the southwest rear portion was layered with ice and liqUid,
coexisting but not precipitating. Echo tops to -40"C or colder
lowered to -lOC to -ZOC in the later stages (from> 8 hrs to 5 hrs
or less). At the time of the lowering, the uniform echo bec8llle more
"spotty," indicative of convective activity. The discussion indicates
formation of precipitation at higher levels (7 km MSL) and advection
to regions downwind (NE) of its origin.
The model results cannot hope to mimic all of the details of this
development, particularly in light of the lack of information about
the mesoscale convergence/divergence fields that may have been
influencing the precipitation develOplltent. Application of the model
to this sounding is made to see what kind of precipitation developtnent
occurs. Convergence is superimposed in the lower levels, divergence
aloft to capture the essence of the formation of any type of stratified
cloud. The presence of the upper low would appear to justify this use
of convergence, but the proper magnitude to use is not known. Also,
the variation of the real cloud tops with time during the 19th would
indicate a diminuation of the convergence after the deeper cloud layers
had developed, which ,,·as not done in the model runs indicated below.
In hindsight, the model is probably capturing the beginning stages of
a system and not the end or more mature stages as observed.
3.2 Model Results - Unseeded Cloud
The natural case (Fig. 4) is characterized by a fairly uniform
stratus deck for the early stage of the simulation (first 30 min).
The vertical n:otion is very weak « 1 m s-l) and shows little organi­zation
during this period. Cloud water contents are also quite low,
generally less than 1 g kg- 1 (0.5 g m- 3). The stratus deck deepens
very gradually with time during the initial 30-min period. Shortly
after the first cloud ice (ice crystals) develops (at -20"C and
shortly before 15 min), the snowfield is in1 tiated, but 1t also
develops very slowly. After about IS min of additional growth of
the snowfield, small turrets become evident near cloud top and are
associated with the development of the snow. These turrets are the
£.!E.:...l: Skew-T plot of 19 February 1980 sounding taken at Villanubla.
Spain. at 1100 G1T. Solid line is temperature; dashed line is dew
point temperature.
17
18
VAL1N2
l~ - - - - - - - - .. - - . -
, .. - - - - .... - .. - . -
: ::: - - - 30
~~ a~eO~~~~;~~~:l~:~~~eV~~~~2c~~t;~~ ~~.i~~~C;~e~i~~lU:eg:~:~:;S
~~~ng°k~~f) ~g~~. c~~~ ~~~t~~~t~~tP(~i~S~e~~~:~a~:~U~:l~~:a~~~a;~:nthan
0.1 g kg~l). The strellJlllines are dashed and indicate a speed of 5 II sec-1
when spaced 1 b apart. The solid lines are cloud outlines where the
R.H. is 100\. The nUllbers in the corner indicate the simulated real
tae and those on the ordinate are height in kll above ground.
_jar convective elell::enu of the sblUlation and inc-Tease in intensity
for a period of time with Il8Xh:UllI updrafts on the order of 10 II 5- 1.
These eleJllents eventually reach the 9 ka MiL level, while the IUin
clotxl deck top is aro\llld 6 k. AGL. Rainfall at the surface is pri­_
Tily due to the melting of snow, although the later portion of the
sillUlation indicates thllt graupel is also fOnled. (The graupel £01'118.
tion processes in the model were inhibited for all cl\Ses with the
19 February 1980 sounding by turning off the aggregation of snov to
fom graupel and by IDllUng the snmoirain interaction production more
restrictive by requiring rain or snow contents greater than 1 g kg-I
instead of 0.1 g kg-I as in Lin et al., 1983.) A radar bright band
forms during the early stages o£"""therainout. Surface accuwllltion
of rain begins during the latter part of tne first nour of simulated
time; I.S to 2.0 IIllIl of rain have accumulated on tho ground at 120 min.
In addition, results are shown for VALINS (Fig. 5), an unseeded
case with time steps identical to the dry-ice seeded cases, (The
simulation of dry ice seeding introduces the fall speed of the ice
pellets which reduces the she of the time step in the model.) The
differences in the results of these two unseeded cases indicate a
slightly enhanced and earlier precipitation process in the smaller
time-step case (VALINS). This may be due to the formation of natural
cloud ice in the model. A te1'1ll in the numerical code concerning the
depositional growth of the ice was found to initiate ice erroneously
at a rate dependent on the nUllber of tire steps, The code has subse­quently
been corrected, but all cases have not been reron since the
IIl8in character of the solution has been maintained. Nevertheless.
the c~arison of CO2 case results ....ith cOlllpatible tiEe steps rests
on fi:mer ground than the AgI cases ",'hich had different time step
intervals and a different total number of tble steps.
3.3 Dry Ice seeding SiDulations
There were three siD.1lations of dry ice seeding 1ll8de on the
19 Februaxy 1980 sounding. Dry ice seeding is siDl.llated by releasing
8 packet of CO2 pellets at a specific location and tille into the sillU­ladon.
The dry ice falls out of the cloud, but results in the pro­duction
of a slll811 amount of cloud ice in the relatively warm region
(-4 to -ISOC).
"
Cases VALICI and VALlC2 were run with the traditional (Fukuta et
~ 1971) value for dry ice effectiveness of 1011 ice crystals per­gram
of C02 sublimed in the cold region of the cloud, Case VALlCS
assumes a greater activity for C02 based on recent laboratory evidence
which suggests that C02 produces 1013 ice crystals per gram of sublimed
materinl within the supercooled portions of the cloud (Bernie Silverman,
priVAte comnunication).
20
:....m~..;...
; . ~
~: The no~seed simulation VAL INS at 30, 60, and 90 min. Syllbols
iiid"lTnes are as explained in Fig. 4.
3.3.1 VALIC} case
In the first. si'/tllJation. dry ice ~.s release<! in II Ibilted area
(volU1l1e) just. to the left of the center of the horlulIItal dOl:illin at
about t.he -8·C level ll't 12 .in after initialh.at.ion of the 1IlOdel. A
total of 104 g of dry ice per kilometer in the non-!IIOdeled direct.ion
lOU released. In this case, only 15\ of the dry ice is sublb::ed in
the sl."Percooled portion of the clouo. The t:luitiWI cloud ice is still
fo~ near cloud top for this case, but is leu than in the no_seed
case. Snow fOI1ll5 slightly sooner and is present at lower levels than
in the no~seed cue. Aside from timing differences, the c1ou<i. develop­ment
is very silflilar to that of the no-seed case, although there is •
tendency, at least initially, to inhibit the deveioplIlent of turrets
near cloud top. Precipitation in the fon, of snow develops slightly
sooner in the dry ice case, and rain appears below cloud base about
3 IIdn SCOller. These differences decrease with time. The dry ice case
wos tenr,inatcJ at 78 min of si1llUlateci time. Compared to the no-seed
results at the same time, there is a S~lO\ increase in 8ccu:rrulated
precipitation at the surface, and the horizontal distribution of the
precipitation has been altered slightly.
3.3.2 VAL1C2 case
A seconcl CO2 silllUlation was run with 9Q g klll- 1 of dry ice
released near cloud top (T" -16-C). The change in seeding location
was I13de to mimic an aircraft passing just above cloud top and dropping
002 pellets into the cloud. In this case, 27\ of the dTY ice is sub­limed
in the supercooled portion of the cloud. Again, S!'lOW forms
sooner and cloud ice form near cloud top.
Figure 6 shows the effec:ts of the CO2 seeding. The top two panels
give the cloud ice field; the bottOlll two, the snow content field for
both seeded and unseeded cases at IS llin, 3 min after the sbllliated
seeding. Also the outline of the seeding agent field is shmm at
I_mn intervals on the seed case, cloud iee panel.
The spread of the cloud ice to lower levels is evident, as is a
secondary center for the SIIOW content field about 10 bl in fY'QII the
left boundary.
Following these changes through the next 15 min or so of cloud
and precipitation development shows detectable differences in the
nUlllerical DlOdel results, but little that could be detected in obser­vations,
except possibly the radar reflectivity. However, radar
reflectivity values are overpredicted in these types of cloud models
(Smith !!..!.!.:..' 1976), so caution IllUSt be exercised here also.
The snow content field at 24 min shows a broader, deeper pattern
in the region 10 u to IS kJJ in from the left boundary (Fig. 7). How­ever,
the cloud ice patterns are very silllilar at the cloud top levels
and differences are hard to detect at the lower levels.
21
22
.~~ .................................... 5 ••••••• , ••• _...... .. •• . ::::::::::::::::::::.:: .. : .. ': ... :.::: =!L=·:·:·:·::·::·::: 1 •.•.•.•.•.•.•.•.•.•.•.•.• _._ •.•.•.•.•.
~ ~(;SE:~i.:~;,:~,~~~.~~,~::,;.~:~~~.;:~~.-~.::,~.,~:'"
'm~ ....................... -.- .
.5 •••••• ,.::> ~ "'0' . .. :..;.........:. -.-:.-=" ==.-, . ' •.•.•.•.•.•.•.•. ' .•.,4 .•.•.•••.•.•.•.•.
o SEED ..:.: ::.:.:'~l,,~~~.~.:.~,~:,;.~:.~·.;:::-..-~' .:,~,,~ .
1D················ ill ...................~.
:::::::::::::::::::::::~:
J .•.•.•.•.•.•.•.•.•.•.•.•.•...•...•..•.•..•.•.• _ •••••••••••.• - . 1 •.•.•.•.•.•.•.•.•.•.•.•.• _._ •.•.•.•.•.
: ~O·SE~D·;:.:}~~,~,i~~;.,,:~~;. ~~:~:i:.:,~: .~,~j: ... [ J .:::.:.:.:.:.:::::~.
:::::::::::::::::~:~~:~::: '= . ..................... - .
~ ~~~D:; :,~:..:,,:i:;.~~;: :',,:i:.:'.:.2:~: ..:.:.:,~.i: ·1' .,.,_ ..•.'...." ...,_. '.''''-
~ t;~O~~~:) (~~~:;~s~~:m::iw:~~ ~~~wn~~~~:~tsi;:~~tion
VALINS and the seed simulation VALleZ at IS IIlin. The dashed
circles outline the seeding agent field at 12, 13, and 14 min.
:~ ::: .~. :.:. ;C:;'.:7:T0
:::: .. : jO .
1 •••••••••••••••••••
:~·:.:.~.L~
·f·····~ :WJL~~
:·~E.~.~·:~·..·~..·~.·~.·~·:·2·?·S·~~~'
) ::::::::::.:':.:::;:::::~:::~:: .,,: ..~.
l~•••••••••••••.
:-_~:~ ..._.....:..:.-~..._." _. ::..:':-_." .. •...............~. .. , ..... ,., ,.,.! .•. , .•.•.....•.•.•.•. :::::::::::::: :". ::: ::.::.:::.::;;~::: == {r .• \~ ::::::::::::::: ~ :::::': :: :',; :.:: :': :.. :.:: :
, .
oEE ~.~ ,~.~.;,~~~_;;,~~~ .. :~:,:~';.:~:n· ..·:~.~. i
!!.&.:2: Cloud icc (top two frUles) and snow content field
(bottom two frUles) cOllparisons between the no-seed siEUla­tion
VAUNS and the seed silllUlation VALIC2 at 24 -.in.
"
24
By 30 min (Fig. 8), the snow patterns are still different, aupented
8UIUJlU showing up in the regions 13 to 16 bI in from the left boundary.
The rain pattern is aho broadened and intensified by the cloud seeding
(upper panels of Fig. 8). The rain accWDUlation (Fig. 9) at 48.0 IBin
shows the additional rain was a large percentage change, but 5111811 in
absolute lUIlOunt.
3.3.3 VALleS case
A third CO2 silllUlation was run with about 8S g km- ll of dry ice
released near cloud top (T. -21°C) at 33 min into the run. Again the
location was such as to mimic an aircraft pass, but at a later time
when the cloud tops were higher and colder. More of the dry ice (32\)
is subli.ed. snow foms and depletes the cloud water. Pndpitation
changes in this case are very siJllilar to the previous case.
3.4 Silver Iodide seeding SiDJlations
A total of six silver iodide seeding siJllUlations were conducted
using the 19 februa%Y 1980 sounding as input to the numerical 'IlOdel.
The AgI is again assumed to have been released by an aircraft, usually
near _10°C at a specified amount. The AgI has no faU velocity as do
the CO2 pellets, hence it advects and diffuses along the flow field
and interacts with the supercooled cloud fields. A discussion of five
of the six simulations follows. The first case (VALIAl) was a trial
run with the seeding II\8terial placed in a location too near the right
boundary and is not discussed further.
3.4.1 VALIA2 case
the _~f~~:~e~~ ;~: fe~·~t~:e:O~nm:~e~;a~~~re~:I::::1n:t
JDaterial W85 released at this location and at this tillle to exatline the
effeets of the seeding in natural snow and cloud ice conditions. At
the release point, there was about 0.05 g kg-1 of snow which increased
in 3 1IIin to 0.1 g kg-I. This represents a few ice particles per liter
of air. Thus, the results are applicable to a cloud in its early
stages of precipitation formation. This appears to be an excessive
llllJOunt of AgI, particularly considering the lilllited area (voIUllle) over
which it was spread. This case is quite interesting, however, in that
it appears to result in a dynamic response to seeding. The cloud ice
produced frOlll JIlOst of the activated seeding material is highly localized
(see Fig. 10). As this converts to snow, the cloud water is completely
depleted in the local source region and in the immediate downstream
vicini ty. This depletion becomes evident about 6 min after seeding
(39 min). An organized updraft begins its develop1llent about 3 min
later. The updraft intensifies rather slowly at first, and then more
explosively about IS min after the seeding lIIaterial is released. This
Jl8jor convective ele_ent, evident at 60 .In, has a strong influence on
the main cloud deck for IlUch of the siDLlated period. The mui1rUlIl
~ ~
) :::::::::::::::::::::::::::::::::::::.
.':::·::::::::o::<i)·· .... ~ ~
o .- ~:_••':::_~~.. ~,_: ::~~_ ' ...._.n c: ~
1 :::::::::::::::::::::::::::::::::::::.
2 .•.•.•.•.•.•.•.•..•.•.•.•.•.•.•.•..•.•.••••• _._ •••••• ~~
'SEED·················~
Q , ..:_.~ ••:'-.::,=,~;;..:..~~=:" .~,,:.:..,......... '.''''''
~:g ...=.:. :.:::..::. • .. : : : : : : : : .• : ::0: :
J .••,, " ." ...... , , .. G- .. ' .,.", .........
2. • • •• • •••••• , • ,
, SEED' •• : : : ?:: .
Q , .. :... ,_ ••_, .....~,:.,:;~..,~;,~:,,:...... : ..;'.':'''' ,. 0' '
25
26
VAllOO21lJll ''''£810 l100CMT
ACCUMULATED RAINWATER AT TIME; 48.00
.00018
"U
or
.w.. .00012 c
"~
Cor
~
:> "~
.0000<>
.00004
.00002
I
II \
,
I
,
I
1/
I
I
o
o
DISTANCE FRO" L.EFT BOUNDARY 11011
~: Rain 8ccUlllUlation at the ground (em) along the xpaxis at 48 min.
'5OII(]line is the amount from the C02 seeded simulation; the dashed
curve is that of the nopseed simulation.
(,
27
Fig. 10: The A&I seed silWlation VALIA2 at 39, 60, and 90 min. Seeding
IIaterial is contoured in th.e bottOlll frllJlle.
28
cloud top for this element is about 10 kIn AGL. As this element moves
to the right and separates from the main cloud deck. it induces a second
major convective element on the left side of the domain. Although this
element does not attain the same cloud top or intensity as the seeded
element, it, too. is quite important to overall precipitation development.
The first rain at cloud base for the silver iodide seeded case occurs
about 12 min sooner than the natural case. and the location has also
been shifted. Graupel famadon occurs at about the sallie time and
location as in the natural case. but less graupel reaches the surface
for the silver iodide case. Total accUllluiation of precipitation is
increased more markedly in this case than for the dry ice cases. Peak
values are increased about 50% and the overall domain value increased
about 20\. The precipitation has also been redistributed considerably
at the surface, although only a few points receive less precipitation.
3.4.2 VALlAS case
This case (Fig. 11) was run with 31.9 g km- l of seeding material,
a factor of 10 less than the previous case. The material was released
at the same location and at 32 min into the siJll.1lation. Again a response
to the seeding is dynamic growth, however, not quite as vigorous as in
the previous case (VALlA2). The depletion of the cloud water is delayed
by 7 min, and the convective element is reduced in size and strength when
compared to VALIA2 results at 60 mn. Both rain and graupel accUlllula- ')
tions at the surface are about 5% less throughout the simulation of
the run, with precipitation starting 5 min later in this run.
3.4.3 VALIA4 and VALlAS cases
These two cases were each run with high mounts of AgI particles
(319 g km- l ) but at later times. VALIA4 was seeded at 42 min and VALlAS
was seeded at 48 min, both at the same location as VALIA2 and VALIA3.
At 5 min after seeding, both cases had seeding effects which again
showed a depletion of cloud water. At 8 min after seeding, the stream~
lines (airflow) in both cases showed a hint of upward motion in the
vicinity of the seeding material that eventually leads to turret growth
and earlier (than the natural case) precipitation on the ground. The
total amount of rain is similar to that of VALlA2 in both cases;
however, the amount of graupel is 25% more for VALIA4.
3.4.4 VALIA6 case
The last seeding siuulation (Fig. 12) was an attempt at modeling
the release of AgI from a pyrotechnic device delivered by an aircraft.
The trail of seeding material is oriented vertically at the same loca~
tion as in the previous cases and at the heavy rate (300 g bll-l ). The
AgI particles were "dropped" at 42 min, the same as that of VALIA4, and
resulted in a very similar simulation to that of VALlA4. The total
precipitation production at 120 min was about 4% less than that in
VALIA4.
2.
Fig. 11: The AgI seed simulation VALlA3 at 45, 60, and 90 min. Seeding
lIatena} is contoured in the bottom frUle.
'" -f -. -"~~ s
~~ ~IH~ ~~T~~ ~;T;~ ~lHssit~; ;~t~~ s~t~ss~t~~ ss-s·~
sssssslDtsssssssssssssssssssssssssssssssssssss
sss'S""S'"s SSS'5~SSS,!;TSSSS-S'S'S'S-S·!t'SS-S""S".(;'Si.5~~.S
3 55SSSS A. SSSSSSSSS5SS$SSSSSSSSSSSSSS$SS$SSSSSS
5SS$SS II>' $5$55$SS$SSSSSSSSSSSSSSSSSSSSSSSSSSSS .. _.. _.. ----·-··.··----··.··.··-··-·····-··-·$055'.4·$
~: The AgI seed simulation VALIA6 at 43, 60, Bnd 90 min. Seeding
lllaterial is contoured in the bottom frame.
31
3.S~
The lack of a significant response in CO2 seeded siDl.llations for
19 February 1980 is intriguing, especially for case VALle3 which should
have produced ice crystal concentrations somewhere between those values
produced in VALlA2 and VALlAS. These results are suspect and 1Ilay be
plagued by some erroneous physical assumptions. The results are. how­ever.
consistent with earlier results for HIPLEX cases••s well as
observations which show little seeding effect if the ice processes are
already active. Another possible e.xplanation of the lack of dynode
response lIIight be related to the much shorter time period over
which the ~ exerts a direct effect cOIIPared to the Ail particles.
Additional siDulations and study are required to resolve this.
The dynamic effects induced by the silver iodide seeding are
apparently the result of the fact that the amount of latent heat of
fusion being released is lIluch more significant in terms of the overall
energetics of the cloud than what is nomally the case in pure con~
vecdve situations with much stronger updrafts. The differences in
heating and cooling due to latent heat of vaporitation associated with
the cOlllplete drying up of the cloud and resultant subsaturated localized
conditions JPUSt also be very important. These stable type clouds with
relatively low water contents thus appear to be Iklre UlC:nable to dynamic
seeding than some convective clouds. It should be noted that :much of
the latent heat release is of an indiTect or secondary nature requiring
the presence of precipitating ice~es. and is not created directly
by the seeding induced direct freedng of the cloud liquid. The lIIfIin
difference here cOlllJlare'd"'tO"earlier attempts at dynamic seeding with
the cloud Illodel appears to be related to the fact that advection is
qui te uniform compared to the much stronger nonlinear character of
the HIPLEX and Florida cases. which have been tested in the model.
The total aJJIOunt of precipitation. both rain and graupel. is shown
in Table 2 for the unseeded case and the seeded cases. The heavy
seeding case (VALIA2) results in 20\ JIOre precipitation on the ground.
The 32 g kr1 seeding rate case also produces cloud stilrolation and
dynllJllic growth. It produces 14\ JIlOre precipitation on the ground with
most of the increase coming through graupel fallout. The natural as
well as seeded cases developed graupel in the later stages due to
the interaction of rainwater and cloud ice near the o·e level. The
convection also aids in causing this graupel fonnation.
Both the natural cloud case and the seeded cloud cRses produce
large convective cells during the latter part of the silllUlations. It
is important to note. though. that the seeded cloud cells have their
roots fairly low In the stratus cloud deck. whereas the natural cloud
cells are DlOre nucerous aloft, not as well organiZed as the seeded
cells. and are smaller in breadth. They do not have as IIJCh
influence on the lower cloud deck as do the seeded cells.
32
TABLE 2
Precipitation Resul ts ~ Stratus Clouds
[
SUll differences noted Within]
30 ain of seed tiM
SEEDING
CASE TIME "(iTn) r."t"m""'""')
CO,
VAUNS No Seed
VALleZ 12
VALIC! 33
35.6
PRECIPITATION
14.1 49.7
".
ALlN2 NatUl'al 39.1 12.1 51.2
ALl'" 33 31. 40.3 21.1 61.4
ALIA:! 32 31.9 39.3 19.3 58.6
ALiA4 42 31. 41.9 25.5 67.4
ALlA3 48 31. 39.9 19.7 59.6
ALIA" 42 300 40.7 23.7 64.4
L
EXMlination of tho model's water vapor field shows that nearly
1 g kg~l of water can be condensed for a 1 km rise. The mesoscale
motions caused by convergence are of the order of ..agnitude 10 em s-l •
This bplies periods exceeding two hours to condense 1 gil of water.
The motions set off by the cloud seeding are of the order _ s-I and
tapIr 10's of IIlin for the condensation of significant water lUIlOUnts.
Consequently, the whole condensation/precipitation process h speeded
up by an order of mAgnitude or lIIOre by the seeding.
The enhanced motion in this stTat~ case was aided by the upper
layer instability. The seeded region was able to tap the instability
in the unstable region more effectiVely than the unseeded clouds and
grow vigorously. Even with no upper layer unstable regions, the
enhanced JIlOtion in the lower stable region appeared capable of
speeding up the cloud life histories and affecting a redistribution
as well as an increase in precipitation. However, lllOdel :runs with
IIIOTe appropriate soundings will be needed to test this last point.
The lD:XIel results also focus attention on the part _esoscale
convergence plays in developing the clouds. Presumably, the conver­gence
values are not constant but are an evolving phenomena within the
target area. Each frontal and trough passage probably induces such
responses.
A full description of the effects of seeding of stratus type
clouds over the entire basin area would probably require 8 1'esoscale
IlOdel with a cloud scale model superimposed. At the present. tille,
such mdels are under developll:ent, but pTObably will not be available
for any planned experiments within the next few years. In the future,
they should prove very helpful for the assessment of modification
potential of such systeDtS.
33
34
4. FIELD OBSERVATIONS AND CLOUD M:lDEL RESULTS,
14 MAY 1981 CASE
4.1 Introductory Remarks
The work that has been done on the 14 May 1981 case is incomplete.
The sounding for 0700Z was the only atmospheric sounding made available
to us initially. so the initial runs were made with this sounding. Not
until much later was it realized that the aircraft data and other
observations were taken nearer the llOaZ sounding data. A few runs
have been made with this later sounding. This timing difference causes
Il\8.ny changes in the numerical results because the synoptic condition
was changing rapidly throughout the morning hours, as described below.
Consequently, the seeding results are available only on model clouds
typical of the 0700Z sounding, which produced clouds deeper and lllOre
active than those produced later in the day. The comparison of model
clouds produced using the 0700Z and 1100Z soundings shows the effects
of sounding and convergence differences on the model results.
4.2~
The aircraft flight S1JllWaries and synoptic data on file at the
WHO indicate that there was a weak upper level 101<.' situated well to
the north of the project area. The soundings (Fig. 13) reveal
instability in the low levels up to an inversion at about ~lOoC.
Cumulus developed early in the day; a lowering subsidence inversion
inhibited deep convection later in the dey. The aircraft observations
revealed numerous cloud development. Two cloud groups were sampled.
The first group was sampled at about noon. Tops were at about
~8°C associated with clouds at 5 Ion width. and turrets 1 km wide.
Liquid water contents of 0.9 g m~3 were S9Jrl}lled with little ice
present. No precipitation occurred from this cloud mass.
The second cloud group was larger (12 k1II in breadth) and slightly
deeper. Cloud elements developed high ice particle concentrations (to
100 per liter) and light rain fell. High values of liqUid water con­tent
coe)(isted with the ice, the water content values ranging from 0.5
to 1.S gm~3. Observer conments and sketches of the clouds sampled
that day indicated cumulus clouds emerging above the stratocumulus
deck with bases ranging from 1.6 km to 2.6 km (KSL) and tops between
4 and S km MSL. in agreement with radar observations.
4.3 Model Results ~ Unseeded Cloud (07002 Sounding)
Figures 14 through 18 show the evolution of the cloud cells on a
C~type cloud day. Figure 14(a and b) shows the general outline of
the IlOdel clouds and the primary precipitation centers. The initial
ctmulus clouds at 63 min grow into a stratus layer at later times.
35
~: Skew-T plot 14 ~lay 1981 taken at Villanubla, Spain. Solid curves
aretlle 0700 GIT sounding and the dashed curves are the 1100 Gl'T sounding.
Telllperature curves are on the right; dew point temperature curves are on
the left.
36
.~
:.:F=?. M~,,'\ ;~~j
• I !!, , •
Fi5" t4a: The no-seed siwlation VAL2NS at 63, 75, and 81 IIin. Symbols
an 1 nes are as explained in Fig. 4.
37
Fig. 14b: The no-seed simulation VAL2NS at 87. 93. and 99 min. Symbols
and lines are as explained in Fig. 4.
38
'.............. -...... -.- - . '=== . ' .• :.: ':. ::<?:::::::.:..... :..::
l 00::' :~"':':''':':. :.: ":0>., ..
2. " , .• {j. •.•.• • .•.•. , ':::: .. : ' :::::::::: - .. ::::' ;7'
o ,.._._ ..._ "':,..;.:~~:..". ':.:=...:..,~:"'_"" '.'''_
~: The cloud water field of VAL2NS at 75, 81. 87, and 93 min,
tlilit'COntouring interval changes at 93 min; units are in g g~l.
Note
,..__ -_...._....-_<.._. ___..,--_ _-
'~ .- . . . ~ , . == . ::~:;~:~~;~::~:::::
:::.: ~~....:~~,;~~~~.•~:. ~.:.:.;:~:....:~,~~ .. ;.
l5'...L.........L................."....,...'....'-J..
: ::::.:::~.::::::::::: '.::~::.::~'::.: . , - ................................... . o " ."". "",. I • ...,_ ••., ,,._......_0-._..'" ._.... '.__ ........ '.'.'" ,'..." ...._. '._'"
~ig. l~: The snow content field of VAUNS at 75. 81. 87. and 93 .in.
ote t at contouring interval changes at 93 min; units are in g g~l .
"
40
'~"""'la ...... . ,. . .
>.......~if= ~.., ,., . J •••• • ".n .•.•. '...... . < :,::.': ... ::. : :,::: :,::::.(BQ::..:.
1 ,,:::::. :... .:'.: ::: ::: ::::: :' ., ." •
o , _,- __' ,, , " .._ ' ... ".._.....•." ..,,_ ...
r. ····] ......................................
::::::::..:::~:::::::~ , ~ ................. .. .. . 2 •.•••••••••••••••••••••••••••••••••• , ::::::::::::::::,'0:":::::::::::::'"
o ' '_:.....:.. .. ',_.~,':,~~~,~~,_'.:~.:._:_l., .',•..:
j:~&. ll; The hail content field of VAL2NS at 81, 87, and 93 min. Note
t at t e contouring interval changes fOT each frame and that the scale
factor changes at 93 minj units are In g g_l.
..~ .... ....... - . - .
.:~ ~ :::::~ ~'~ ~ :~ ~ ~ ~ .~ ;:::~ :::;~i~ ~ ~ :~ ~ :~ : , ::.. . . . .:~ -_ -. ::. . , . ' .,.,__'_-,,_ _,.._. , .
.~...................................... , -.- . .= . ............... -.- .
J .•.•.•...•.•.•.••.•...•.••••••••••••••.•.•.•.• . 1 ..•.••••• , •.• _ .•.•.•• _ .•.• _.
:; :.:: ~.~·..:~~~~~-:~·.M:.~;:~:~:.:~~: ';
1..·.·.·.·.·.·.·.·.·.·.·.·.·.·.·.·.] 5 •••••••••••••••••• . : :: :::::::::::::::
J'. .•.••••••••••••••••. J .•.•.••.•.••••••••••••• ~~ . ' ... ···~·······81
o < ._ ..,_ .,,,_,_ ,__ ,,,__....~"'....,._ ' ...
FgS. If The rain content field of V~L2NS at 81, 87, and 93 min. Note
t at t e contouring interval changes at 93 Idn and the scale factor
changes at 87 IIlinj unit" are in g g_1.
41
42
At least five cells can be identified in the cloud water content fields
at the earlier times (Fig. 15, 7S min). The cloud top extends to over
5 km (AGL) or 5.9 km (MSL), which is too deep compared with the obser­vations
later in the day. This 15 caused by the model convergence
(5 x 10- 5 5-1) and the moist 0700Z sounding used for the initial
conditions.
These cells evolve in a realistic fashion. The snow content
(Fig. 16) is the first precipitation field to form, followed by
graupel/hail (Fig. 17) and then rain (Fig. 18) in the lower eleva­tions.
Only a few mm of rain and,graupel accumulate on the ground
after 30 min of cell development (63-93 min).
4.4 Model Results - Seeded Cloud (0700Z Sounding)
Figures 19 through 23 show the seeded case results. The cell
centered about 6 km from the left boundary in Fig. 14a is seeded with
241 g of C02 (per km in the unmodeled y-direction) at 66 min. The
seeding material is initiated in the model at about .3 km height (at
about -lO·C) in a box pattem, as described above (Sec. 2.3.1). The
CO2 forms cloud ice which interacts with the supercooled cloud liquid
to form snow and then graupel. The seeded cell forms precipitation
about 6 min earlier than its unseeded counterpart.
At 7S IDin. the depletion of the cloud water (Fig. 20) by the snow
and graupel is quite evident in the seeded cell compared to the unseeded
cells. By 81 min in the unseeded case (Fig. 15), the "seeded cell
counterpart" has depleted the liquid water also, because of the natural
precipitation processes, primarily accretion of liquid water by snow
and graupel.
A light rain shower is depicted at 81 min in the seeded case at
about 11 km in from the left boundary (Fig. 19). The graupel field in
Fig. 22 and rain in Fig. 23 show that the shower from the seeded cell
is over by 93 min. A similar, but lighter, shower shows up in the
unseeded case at 87 min (Fig. 14t) , which also ends by 93 min
(Figs. 17 and 18).
4.5 Seeding Potential
4.5.1 Method
Using the 07002 Va11anubla sounding, the aircraft (AlC) data from
1100 to 1330, and the radar data from 1100 to about 1400 combined with
numerical model results allow estimates to be made of the seeding
potential on this day and to be compared with the radar and aircraft
methods of estimation.
Fig. 19a: The CO2 seed sbllUlation VAL2el at 75, 81, and 87 min. Symbols
and hnes are as explained in Fig. 4.
"
Fi~. 19b: The CO2 seed simulation VAL2el at 93 and 99 min. Symbols
an hnes are as explained in Fig. 4.
.~ .-............... . .....•.•.
:::~~
J a·.... ." .•."..... .......
2 : .' : ".::::'" •• : ••••
: '::::.,' .•or;;: ~:::::::::. ~::::';1' -,_ _.",__.-..'_.,._- _._.. ...
, '_..,' .(".,......_. ,-, _.•, ' ... -.., " _...
.~.~=::::::.:..:.:.'::::::.:.:.:.:.:.::::::::: s::::::::::::: .
. . .. . ,. . .. .,.. ". ...n." .
l • " ••_~. • .
> :. ' • ", ., •• ::. • - ';::. ; :::.~ o:.'::::.:.·~;
, _ ..._.-_0.__" ,.._. _ ...
~: The cloud water field of VAL2e} at 75, 81, 87, and 93 Din.
~.t contouring interval changes at 93 min; tmits are in g g_1,
4S
46
___ .•.1 _ ,_,,_ 0._"''''''''' ._.....
..., _•. , " '.1"''''
1.·'..·1·-1·T-I·~·• ·•·••·••·•·•.•·••·.•·..•···.·. •·.•]·.•. .' ......... . ~, .
:::::::::::::~::::::::::::::::::
:::,::, :iL~~,~.~: :!•.~.~i: ~..:..;.:~:~~u:,..:.:,~j: ~~ . ..., ' " , ..
Fig. 21: The snow content field of VAL2el at 75, 81, 87, and 93 lIlin.
NOte't1i'at the contouring interval changes at 93 min; units are in g g-l.
47 ·1Ii·tJi ..... - ,.,. . . ~ . .
.==.. =. :!.l.>~:'~ fhTy~.
o ,_,_ -4.'_....,':',:.;~~_~,~:',.;.....,~_;.., 0<...... '.'__
1..·.·.·.·..·.·.·..·.·.·..·.·.·.·..·.·.·..·.·.·.·..·.·.·..·.·.·..·.] ~ ", .
:j~~~~~~~~:..~~~»<
" ~ ~
o ';';' i' .~·;~l~~~·:.:~~:~~:~:~~i.:.:~~' 7
!!8.:-..1l: The hail content field of VAL2el at 75. 81. 87. and 93 min.
Note that the contouring interval changes each fnme and that the scale
factor changes at 81 and 93 min; units are in g ,-I.
48
.~ 5 ••••• _ ••••••••••••••• _._._ ••• _ •.•••••. ·::::::::::::::::::::::::::::::::::::::
) :::::::: .':."'::","::::::::':'::::::.
2 • •••• •••••••••••• _._ 0'_ .•.•.•. ,
o __.... _~'~,..:..~~:::.',::'":"" ; ..:".:-'" -... .. •. '....,
·1..·.·.·.·.·.·..·.·.·.·.··-.·-··············-·.-·····]·. ·, -.- -.-.- . ::::::::::::::::::::::::::::::::::;::: :~,~, U._~."l~j~l:l.,.I,',l., ~.~.
··,:1:::·:.:"·:. ::::::::::::::::]:.•:.....
) .,-..,.- -.-. . - ..
2 •••• ;ii()o ...•.•.• _.
::,:: ,.:_._.,.::..;g_...;~,-=.;,::.:, ...:....:.::,~:.'
1\;0 types of cells are envisioned -- first, those that have no
(or little) nat.ural ice and are not producing precipitation; second,
those th1t have natural precipitation, but that 1118y be seeded to pro­duce
precipitation embryos earlier in their development than would
have occurred naturally.
At this ti.e, lllOdel results are only available for the second type
of cell because the 0700Z radiosonde sounding is representative of
conditions that are IllOTe lIIoist and with a deeper cloud layer than the
conditions eXisting later in the Vall.doUd area (near noon). Later
IOOdel runs 10'111 include a more represent:atlve sounding for the midday
conditions (this work is currently being done on the CRAY-l at NCAR).
Even wi'thout these later coaputer results, asslJq)tions, extrapolations,
and speculations are ..de concerning the seedabl1ity of the smaller
clouds.
4.5.2 Aircraft analysis analog
first to be described is the Ilodel estimate of increased rain
froll ''non-raining'' clouds. The technique is to use conditions froll
the J:lOdel results before significant precipitation has fOnled, and to
asSUlle that the ultimate precipitation from the cells is produced by
artificially supphed ice embryos (although in the model results the
ice embryos actually come from high-level ice cloud produced by the
model's convergence field). The area of the active cloud cells is
taken froll results at 72 Jain, as is the average liquid water content
and depth of the clouds. The tite for precipitation fOrJlllltion and
fallout could be taken frOID the evolution of the cells. Thirty IIinutes
is used, in agreement with the A/C analysis. The model results suggest
a longer period, continuous type of rain upon which are superimposed
showers of shorter duration. The model convergence probablY is
responsible for this. A total tiPe period of 6.5 hours, from 0900
to 1530, was used in the AlC analysis of this case (referred to as
Cl7 in Sec. 5.3 of PEP Report '28). The radar analysis used data
fTOlll 1100 to 1400 local time, over which period 8\ of the area was
covered with echo.
The aircraft Illethod uses an equation
49
(4-1)
where LiiC is the mean liquid water content (g .- 3) at the upper levels
of the cloud (defined more preciselY in PEP Report '28) and AH is the
depth in ltJD. The result of (4-1) is the amount (depth) of liquid water
per unit area in a single cloud or cell.
so
The W-value is then used to calculate the rain increment, AR.
that could be produced area Wide, from Eq. (4-2); i.e.,
(4-2)
where £1 is the fraction of the 5&q)led area having seedable conditions,
£2 is the fraction of tbe total area having similar conditions to those
sUlpled by the aircraft, T is the total period over which the conditions
existed, T is the cycle time of the cloud and precipitation processes,
and F is the fraction of the total area appropriate for the model dOJllain.
POl' this particular situation at 72 min [after model initiation
with the 0700 sounding, convergence of 5 x 10- 5 s-l. and random per­turbations
in t~erature (iO.SO 1llaXimullI) and hUlllidity (t7\ m.a.xilDl.Ull)
produced eveTY 30 mn if no clouds are present in the maoc!]. the
followins values are obtained fro. tfle wodel output:
Ul'C" 1 g kg- 1 ~ 0.8 g 11- 3
tJ:I .. 2.2 krn
and W .. LWC Ml
co 1.76 lilt
(4-3)
where the factor of 1/2 is dropped from (4-2) in (4-3) because of the
availability of the LWC profile in the model clouds.
The factor of ft is estimated as about 22'. arrived at by taking
the portion of the grid covered by the cells at 72 min and squaring it
and dividing by the domain length squared ("'9 b:I of cloud cells out
of the 19.2 b. model domain). The f2~factor is taken frOll the aircraft
and radar data; a value of 0.8 is used in PEP Report 128. Tis 6.S hrs
and t is 30 JIlin. so that 13 cycles of precipitation are hypothesized.
F is (19.2 kz)2 divided by 31416 kz2 indicating that only one such
area in the entire region is asSUlPed in this case.
The result is
AR ...047 .. 4.7 X 1O~2 mm
This is about three times the value calculated by the Wyoming Ale group
and is probably a result of the ~re moist sounding used for the
initial conditions in the model.
The actual rodel precipitation can be corcpared with this
4.7 x JO-2 mm value. After 30 min (at 93 ll'Iin). the average rain and
grflupel fallout accumulated on the ground is about 0.28 mm (0.12 WIl
rain and 0.16 D'\1!l groupe!) over the entire 19.2 km wide domllin. TIds
yields a tlR1 estimate of
51
llR} " ~ TFf,
= 0.28 IIIIl • 13 • 0.0117
.. 0.0426 1lIlI ~ 4.3 X 10-2 DI
4.5.3 Radar analysis analog
(4-4)
An estimate of the extra rain from the precipitating cells is
D....de by comparing model results of seeding a cell with CO2 and COIIlp
paring ldth the unseeded lllOdel cell. and then extrapolating the
results to the entire radar observed area.
lhe unseeded IIOdel cell produces 0.16 ftIl rain and 0.15 IlIIl &Taupel
at 93 mn. The seeded cell produces 0.29 Rl rain and 0.22 graupel at
93 min. The difference is 0.13 Ell! in r8in and 0.07 n!I in graupel -- a
total of 0.20 I'lIlI (bRo>_ AssUlJl.ing thn this difference applies to all
the cells (all cells being seeded ill an ideal experilllellt). then the
extra rain averaged over the ent! re are~ (8\ of t.he tot.a) area is
covered by radar echoes) over a 3-hr period is
t.R2 " 1I~ TF/T (Fraction of Area)
::: 0.20 lllD'l • 6 • 0.08
• 0.096 :: 9.6 x 10-2 ...
The total change of precipitation i5 the 5U11 of the two. IC'hich is
(4.5)
The radar RVIA analysis for this case in PEP Report '28 yields
an increase of 47 x 10-2 1IIIl (frOlll a 0.158 _ hr-1 increase in areal
averaged rain rate for a 3-hr period).
52
4.5.4 Discussion
This preliainary exercise has indicated how one lIIight use one,
two. or three-di.ensional cloud model results combined with aircraft
and radar observations to estilll8te the seeding potential of a region
during. particular day. For an extrapolation to seasonal results,
IllOre case study days should be analyt.ed and an average effect deter­mined
for the characterisdc clouds in the reglon -- the Mi. AC. C,
and B type clouds. Probably, at least 5 to 10 days would be needed
for each type of cloud.
The results shown here use a 2-D, tiEe-dependent cloud model.
but the possible use of I-D or 3-D, time--dependent cloud models would
follow the same procedures. but using more or fewer assumptions, as
appropriate, about cloud coverage. nUllber of cells, etc.
Table 3 gives a summary of the model, Ale and radar RVIA results.
4.6 Model Res~lts - Unseeded Cloud 1l00Z Sounding
Figures 24-27 show the numerical results for this case. Figure 24
depicts the cloud outline 30~66 min after model start up. The symbols
Sand· represent snow and rain contents greater than 0.1 g kg~l.
respectively; the stre8ll function is given by the dashed lines at
inten'als of 5 x 103 kg m~2 s-l. This model run was initiated
with the lWOZ, 14 May 1983 sounding with heating and evaporation
rates at the earth's surface approxiJaating those for the site.
Saall clouds topping out at about 2.0 to 2.6 bl (AGL) (station
height is about 850 m) are present at 30 mn. which grow eventually
to more than 4 kill by 66 mn. A s1liall cloud 11 klII in from the left
boundu)' grows to only 2.5 bt and then dissipates, foming negligible
precipitation. The taller clouds produce over 1.0 DII of peal:. accumu~
lated precipitation by 60 mn. Cloud bases range frawl 0.4 to 1.4 D.
about 0.4 Ul lower than the obsen'ed clouds indicating IllOre water
vapor in the model atmosphere than in nature on this day.
Figures 25-27 show the cloud water. snow. and. graupel/hail
contents. Values of 1 to 2 g kgp1 occur in the cloud water and a
few tenths of a g kg-1 in the snow and hail contents.
Figure 28 gives instantaneous cross sections of snow. graupel,
and cloud water through the central cloudy region at various model
tiJlles. 42 min - 63 min, and at heights corresponding to the level at
which the Queen Air aircraft flew. Comparison of this figure with
Fig. 29 taken from the real data (and is a time cross section, but
with I IlIin "4 0) shows the IOOdel disturbances to be of the saJlle
scale as those in nature. but to have too large cloud liquid water
contents (even after allowance is made for the IllOdel values in
g kg-1 to be converted to g m- ~. Also, the change of cloud water
53
TABLE 3
Sta:I&ry of Results·
llR Aircraft (AlC)
R Iok>del Results.
(NC) Technique
PRECIPITATION (Areal Averaged)
(Uni ts 10-2 DIll)
(30-1I1n cycle) (36-1110 cYcle)
1.4
4.7
EQlJATION
(4-3)
llRl Model Resul ts
R2. Model Results.
Radar Technique
R2. Radar CRVIA)
4.3
9.'
47.0
13.9
12.0
10.8
22.8
(4_4)
(4-5)
-- PEP 28
(4_4) & (4-5)
~bserved Areal
Averaged Precip.
__________ 13 _
!Model Precipitation 14.9 22.0 (4_S)t
Results I
·See text for explanation of entries. .
t (4-5). but with unseeded average precipitation replacing ARo. I
the difference in precipitation between seeded and unseeded cells. I
54
1i:··:····~····2····:·· 5-:~
."" '''''''''''''' " ,,,,;12
Fig. 248: The natural simulation of VAL3N2 at 30, 36, 42, and 48 min.
Symbols and lines are as explained in Fig. 4.
55
Fi5" 24b: The natural simulAtion of VAL3N2 at 54. 60. and 66 adn. Symbols
an hnes are as explained in Fig. 4.
56
,..' '_ .•. _ .,,, . 0>, , ,,,, _.0>, ,, •.,,..,,.•. _ .... ,., ,."" ",_ .." ..."
~ig. 2~a: The cloud water field of VAL3N2 at 30, 36. 42. and 48 JDin.
ate t at the contouring interval changes at 36 min; units are in g g~l.
57
, - '••_ ._,., , ..' q _ " _ .. -.._ , ..
._ _' .._..•,._ _ _- _ ...
,.._._., _ .,_ _ , _ .., " , 0.'_- , ..
Fig. 2Sb: The cloud water field of VAL3N2 at 54, 60, and"66 .dn. Note
that the contouring interval changes at 60 min; units are'in g g-1.
58
'_'_'0.'_"''' .."_'"" ""' ", , ' ... ,_."."••, __
",.J ,..' '_ ,_..,,, .,., """_,." '."".., ,.."." _",
F~. 2~a: The snow content field of VAL3N2 at 36, 42, and 48 rain. Note
t at t e contouring interval changes at 42 and 48 min, and that the scale
factor changes at 42 and 48 min; units are in g g_l.
a
........-.•._ ._,..__.-_- -_. __ _ _... '.'--
:E~~~
,_,__._..... 0..___...-._."_M_._...•• __... " .." .... ..__
FiG' 26b: The snow cont.ent. field of VAL3N2 at 54, 60, and 66 min;
unltS are in g g-l.
"
60
, _ .."..,...•,,, •."'"0"0.0..0.<...0,'>.._..-", .." ,_,,,,,.,.,..,, ""',,,..,••. '.'_'"
<."....._ .•.._.0> '••.._......."...,.......,.......""-",, ,,._._..""."""""" '.'_'"
Fix. 27: The graupel/hail content field of VAL3N2 at 54. 60, and
66 min; units are in g gpl.
o
42 MIN
(1320-1323) SNol.. 45 MIN . GRAUPEL. ,,,g1-'] /\
j '\~
48 MIN
(1325-1328)
51 MIN
SNOW .. . GRAUPEL.
[gkg-']
54 MIN
(1331-1335)
• LWC i\ . -+--[~.~gk~'1 - f- JUV\ ,/\ j\. j',f{\
o 35191113 351911130 3 5 1 ~ 11 13 3 5 7 9 11 13 11 9 7 5 3
~, Model output of ~n(l'l<, gra"l'eJ/hail. and cloud liquid lIater oonUnU along a constant
height corresponding to the drcraft ullpling 1""1. Model rimes are nored in ucll block with
the conesponding aireraft penetration ti....~ in parenthese, (u given in Fig. 29 and arbitrarily
_tctl"dtlere). Abscina gives values inbifrOllthe left border of tile dOlllain, except for the
lastblocl<.
62
with flight direction and the associated change in ice particle
concentration is clearly evident in Fig. 29. but not well repre­sented
in Fig. 28. In several locations in the model results. low
liquid water contents correlate with high snow and graupel contents,
as is also evident in the observations.
4.7~
These results with different soundings have indicated the sensitivity
of the model (and the atmosphere?) to the initial conditions and the
mesoscale convergence field. The 0100Z sounding with convergence
produced much stronger convection than the 1100Z scunding without
convergence. Even so, the first model clouds in the earlier sounding
were not llheavy rainers" and could be used as examples of what might
occur with C-type clouds.
The seeding effect of the dry ice was to start the precipitation
earlier, thus leading to a longer period of precipitation and DlOre
rtLinout eventually, consistent with the results of Kopp et a1. (1983).
No dynamic effects of the seeding were evident. These results with the
0700Z soundin.q are appropriate for clouds in which natural ice would
not fom in clouds until temperatures of -20"C or lower were reached.
Cloud seeding tests on the UOOZ sounding clouds wiU be more appro­priate
for the actual clouds which fomed on that day and in which
natural ice was observed at temperatures as high as about ~lO"C.
However, those tests have not been run yet.
o
ATUAEnoo----------------------------------------..,--------
1°01 ~ ~
_~Ol I I I J I I I I I I I I 1 [ I I I [ I
~~i:~~O;h:r=~~A~~e~h~~~~~J"~;~ :~~ali:~a~~ Mari:..l::~~ra~ep~~~a~~~/;~;::re
nating <!i:rections £I'OJII one sepent to the next, starting with a south to north penetration.
Ti...s an inl!inutes an<! the tlcl:urks about 4 blapart, cOJ"respond1ng to an aircraft speed
of 7011.-1.
64
5, StMlARY
The n\ll:!lerical 5i~latlons of both an A-type and a C-type cloud
systelll have revealed a cloud seeding potential in clouds with and
without natural cloud ice. The simulations have Shot>l1 a pot.ent.ial for
dynamic effects in a nearly :-oist adiabatic. at:llosphere which produces
prl1lltlrily stratifora clouds. This is an effeet not previously con­sidered
for such clouds and needs further modeling and field verifi­cation.
If the theory is supported. the seeding of stratified clouds
could take on increased importance. because the signal is so clear
and should be easily detected in field experaents. The statistical
and physical tests should be able to give significant answers in a
relatively short time.
More needs to be done in the studies of both C- and A-type cloud
5ystelllS. The seeding siDlulations on convective clouds are very
incomplete. Investigations of how the cloud seedin& works on clouds
with some natural ice are necessary. The relative illlportance of the
Ilicrophysical and dynamical effects of the seeding should be detect~
able in cloud seeding simulations (Orville and Chen, 1982) and should
help in understanding the cloud seeding effects.
Further applications of these results to the PEP data set are
possible. The nUllber of days with lIIOist adiabatic conditions in a
particular season could be detennined and the seeding potential for
that type of cloud estilllAted. After further slllJJlations are done
on C~type cloud days, mre quantitative predictions could be made
of the seeding potential for such days.
Whether or not further studies are done on this data set,
significant results have been produced. New insights have been
gained regarding cloud seeding effects. The work with models and
observations is an ~runt start and shows a new way of obtaining
estimates of cloud seeding potential.
.5
ACKNOWLEDOONT
Acknowledplent is made to the World Meteorological Organi:r.ation
and to the National Science Foundation under Grant Nos. ATM-7916147 and
,,'1)1.8311711 for funding this effort.
We acknowledge Fred Kopp's fine work in doveloping the dry ice
seeding silllUlations used in this study. We thank Mrs. Jote Robinson
for her excellent assistance in report preparation and typing.
AcknowledgJDent is made to the National Center for AtllOspheric
Research, which is sponsored by the National Science Foundation, for
the computer time used in this research.
66
6. REFEREn:ES
Berry, E. X., 1968: Modification of the "ana rain process. Proe. 1st
Nat!. Con!. We•• Modif•• Albany. Amer. MetC<lT. Soc., 81-~
Bigg, E. K., 1953: The supercooling of ....ater. hoc. Phys, Soc. London.
~688-694.
Blair, D. N., B. L. Davis, and A. S. Dennis, 1973: Cloud chamber tests
of generators using acetone solutions of AgI~NaI, AglwKI. and
AgI-NH..I. J. APEl. ~tcor•• .!l. 1012·1017.
Chen, C. H•• and H. D. Orville, 1980: Effects of lIesoscale convergence
on cloud convection. J. Apr}. /o!eteor., .,!!. 256-274.
federer, B., and A. Waldvogel. 1975: Hail and raindrop she distributions
froll a Sdss wlticell ston.. J. Apr1. Meteor.,.!i. 91-97.
Fletcher, N. H., 1962: The Physics of Rain Clouds. Cmnbridge University
Press. 390 pp.
Foote, G. B., and P. S. du Toit, 1969: Tenainal velocity of raindrops
aloft. J. !.ppl. Meteor .• !. 249-253.
Fukuta, N., 1\'. A. Sc».meling, and L. F. Evans. 1971: Experimental
detennination of ice nucleation by falling dry ice pellets.
J. Apr!. Meteor •• .!2J 1174-1179.
Cunn, K. L. S•• and J. S. Marshall. 1958: The distribution "'ith size
of aggregate snowflakes. J. Meteor •• .!!.. 452-461.
Gw!n. R., and G. D. Kinzer, 1949: The terminal velocity of fell for
water droplets in stagnant air. J. Meuor., !o 243-248.
Holroyd, E. W. III. A. B. Super, and B. A. Sllver:man. 1978: The
practicability of dry ice for on-top seeding of convective clouds.
J. App1. Meteor •• 1:L 49_63.
lisie. E-Y •• R. D. Farley, and H. D. Orville, 1980: NUEerical simlation
of ice-phase convective cloud seeding. J. Appl. Meteor., .!!'
958-977.
Kessler. E., 1969: On the distribution and continuity of water substance
in atmospheric circulations. Meteor. Monosr.. ..!.Q., 32. 84 pp.
Koenig, L. R., 1971: NUIIlertcal modeling of ice deposition. ~
~,~226-237.
67
Kopp, F. J., H. D. Orville, R. D. Farley. and J. H. Hirsch, 1983:
Numerical simulation of dry ice cloud seeding experiments.
J. CHmato /Ppl. Meteor., il. 9, --.
Lin. Y-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization
of the snow field in a cloud model. J. Climate App!, Meteor., E.
6, 1065-1092.
Liu, J. Y., and H. D. Orville, 1969: Numerical modeling of precipitation
and cloud shadow effects on mountain~induced cumuli, J. Atmos. Sci ..
~. 1283·1298.
Locatelli, J. D., and P. V. Hobbs, 1974: Fall speeds and masses of solid
precipitation particles. J. Geophrs. Res •• J.2.... 2185-2197.
Marshall, J. S •• and W. M. Palmer, 1948: The distribution of raindrops
with size. J. Meteor., ~ 165-166.
Musil, D. J., 1970: Computer modeling of hailstone growth in feeder
clouds. J. Atmos. Sci., n.. 474-482.
Orville, H. D., 1965: A numerical study of the initiation of cumulus
clouds over mountainous terrain. J. AtIlIos. Sci .• ll. 684-699.
, and J-M. Olen, 1982: Effects of cloud seeding. latent heat
--or-fusion. and condensate loading on cloud dynamics and precipi­tation
evolution: A nU2llerical study. J. Atmos. Sci-., 39.
2807-2827. -
-'and F. J. Kopp, 1977: Numerical simulation of the history
of a hailstorm. J. AtlllOs. ScL. ~. 1596~1618.
Saunders. P. M•• 1957: The thermodynamics of saturated air: a
contribution to the classical theory. Quart. J. Roy. Meteor.
~.ll> 342-350.
smith. P. L•• Jr., D. J. Musil, S. F. Weber, J. F. Spahn. G. N. Johnson,
and W. R. Sand. 1976: Raindrop and hailstone size distributions
inside hailstorms. Preprints Intn!. Conf. Cloud PhySics.
Boulder, CO. Amer. Meteor. Soc •• 252-257.
Srivastava, R. C•• 1967: A study of the effects of precipitation on
cumulus dynamics. J. Atmos. Sci., ~, 36-45.
Wiin-Nielsen. A., 1~79: On phase speed errors due to various time
differencing schemes. Numerical Methods Used in Atmospheric
Models, Vol. II, GARP Publications Series No. 17, WMO. 438~473.
Wisner. C., H. D. Orville. and C. Myers, 1972: A numerical model of
a hail-bearing cloud. J. Atmos. ScL, ~. 1160·1181.
This info1'lll8tion provided in accordance with
Executive Order No. 75-6, State of South Dakota.
Office of the Governor:
(a) Total cost per copy (preparation 6; printing)
(Pre-press estimate) ., $3.19
(b) Total no. of copies .. 400
(e) Purpose" Present research results
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Report 83-4
HtM:RICAL SIMUlATION OF PEl' CASES ANI>
CLOUD SEWING EXPERIHUiS
8y: H. D. Orville, J. H. Hirsch,
and R. D. Farley
Prepared for:
Weather Modification ProgrUllle
WOrld Meteorological Organization
Case postale No. 5
01-1211 Geneva 20, Switzerland
Nov_er 1983
Purchase Order No. 29462
.>
Institute of Atmospheric Sciences
South Dakota SCh~l of Mines and Techn<>logr
Rapid Citr',.:South Dakota 57701
Report 83-4
NtHRICAL SIMUlATION OF PEP CASES AND
CLOOD SEEDING EXPER~i'S
By: H. D. Orville, J. H. Hirsch,
and R. D. Farley
Prepared for:
Weather Modification Progr8Jlllle
World MeteorologicaI Organization
Case postale No.5
01-1211 Geneva 20, Switzerland
Novellber 1983
Purchase Order No. 29462
Institute of Atmospheric Sciences
South Dakota School of Mines and Technology
Rapid City, South Dakota 57701
..
•
•
.,!
-,. '. l'
: .
n,lFAQ:
".~ ~rinl MoteU... Cnup of tho r••tSUA-. or Al_..~ti(:
SdHC'u (lAS) at ct-A: Souu. Ddot,. khool O€ ..~ -.4 Ttp''' OOPUl). -.tdc' if .pc>6tONd by
, .. tuft'.." .f Aecl....Uee ct t~ UIIlted. ,SUt.. ~u o( 1M
Iated.,.
~ wen. ..... ac.. 1JI U. .arly It..,., of eM .rrort .."" ru.Ut
rcport.d It a IDMt!1:;f: l.ld I .• MU'~' l'ta U ..,lexity and more realistic air flows than the one­dimensional
models. These 20T cloud model solutions involve considera­tion
of cloud cell interactions and microphysical/dynamical interactions
on domain scales of a few 10'5 of kilometers (using 100 m to 200 m grid
intervals) and over time spans of a few hours (time steps of a few
seconds). Even so, some compromises with the microphysics have to be
made to allow many operational runs of the models and a significant
nUJl1ber of cases to be tested.
The 20T cloud model results reported on here use simplified
procedures for the microphysics as well as simpler 2-D dynamics. The
treatment of the precipitating particles relies on the bulk water
technique, ,",'hich essentially assumes that the precipitating water or
ict' content is distributed in drops or ice particles that fit an
inverse exponential size distribution, albeit a different one for
each type of precipitating content considered. This maKes impossible
the consideration of the many shapes, crystal habits, and variable
densities characteristic of snow, graupel, and hail. Rain and snow
are treated in separate equations. The graupel and hail field are
considered as one and are treated in one equation. Small hail con­tents
«1.0 g kg-I) are dominated by graupel and the mass weighted
mean size (0 = 3.67/"G) for larger contents is rarely larger than
several millimeters. By convention, hail has a diwneter of 5 lIlJlI or
more, but we refer to all graupel, ice pellets, frozen rain, or hail~
stones as ''hail'' in the hail content field. Further details of the
method Bre given below.
In the sections to follow, a description of the cloud model and
the seeding: technique is given followed by sections concerned wi th
the natural cloud model results and comparison with observations,
the C02 and AgI seeded cloud results, and a general discussion
and conclusions.
~.·.[,~~~::r·"~~~'1r~~'::~,··
.,~. , . ;,_. . :.. ...~. I
"'.';:,
'., :
. it>
.. .*
'.,
.,
'.
2. NOOn DESCIU PTION
2.1 General Aspects
The cloud model is two-diJllensional, ti'lle·dependent with bulk water
microphysics. The dOlllain of the model is 19.2 h in both the X and Z
dimensions with a 200 m grid interval. AtlJlOspheric wind, potential
telllperature, water vapor, cloud liquid, cloud ice, rain, snow and
graupel/hail (in the fono. of ice pellets, fro ten rain, graupel, and
SJDall hail) are the main dependent variables. The model has been
developed fro. the "·orks of Orville (1965), Liu and Orville (1969),
"isner et a1. (1972), Orville and Kopp (1977), and Lin et a1. (1983).
Extension OTthe node1 to sillUlate deep convection has bee'Ji'"Ude using
a density weighted streaJll function (Olen and Orville, 1980). The non·
linear partial differential equations constituting the llOdel include
the first and third equations of motion, a thermodynuic equaticn,
and water conservation equations (for its three phases).
The llOdel has been designed such that aesoscale convergence can
be superiJZlposed in the lower levels and divergence in the upper levels,
,.-hlch can result in stratus.type clouds being forced under certain
atlllOspheric conditions (Oten and Orville, 1980). The DOdd is there.
fore capable of silllUlating the stratus or nimbostratus.type clouds
found to be typical of cold late winter or early spring. conditions in
the Spanish project. The 1Il0dei has also been developed to include a
seeding agent, either dry ice or an ice nucleant such as silver iodide.
These are described, respectively, in Kepp et a1. (1983) and Hsie et
~ (1980) and outlined below. - - -
The production of cloud water, cloud ice, rain, snow, and
precipitating ice are sh:ulated using the bulk water techniques. The
production of rain from cloud water is simulated using equations based
on the work of Kessler (1969) and Berry (1968). Graupel/hail is formed
by freeting rain to ice by means of an equation due to Bigg (1953), or
by aggregation of snow or capture of snow or cloud ice by raindrops.
An approxiJlltltion to the Bergeron.Findehen process is used to trans­fOn!
scme of the cloud water into snow. Growth of hail is governed by
equations for vet and dry growth ()!usil, 1970). Cloud water lIIay be
transfo~ to clOlld ice in the region between O·C and -40·C using an
equation developed by saunders (1957). HOIIIogeneous freeting takes
place at the -40·C level. Rain, snow, and graupel/hail possess
appreciable terminal £011 velocities. Cloud water and cloud ice
have tero te:minal velocities and thus travel with the air parcels.
Evaporation of all fol'P.5 of hydrometeors and melting of snow and
graupel/hail are also siJlulated. Figure I and Table I show the
cloud microphysical processes sinllated.
~
0..1Jl
Q. i
~ ~
rf' o..rr.
....
::> a!'""
WATER VAPOR
CLOUD
ICE
~; Cloud physics processes silllUlated in the Model.
1'Or&i\ explanation of the sYlllbols.
see Table 1
hy to F1l:llr~ I
Heltlq:ofosltJonal Crowtll of cloud Ice U ~'"Pe1l,eoCclOdddepudJ..... onUla_t
of ..au.. .
Aco:«UonoCcloud"aterbrnin.
Eupor.tionofuln.
AccreUon of,1IO'Ii by rdn: produce' Itlupel Hnlno.. snOllexceed.thra,hold
andY·Yo •
Accretion of c1oud ..t ... by s""". proclucu ... trT' TO or ...b lfY ~ TO'
Aho eM.on~••_ -eltlflJ lor .T ~ YO'
nereUoe of raiA by ._. For T • TO' proct..::es rnupel If ...iII Or s_ eKeeds
~~:::~d; if not, produces 5_. For T !. To' tu 'CCrlrted "ater ellll.a..cu ._
Acc..etlonofcloudlc~by&_,
Autoconversion (a.uresatlon) of cloud lco to fOTll.now •
....lleronptoeen(deposltlonllJld ..l.aUs)-transferofcloud"aurtofor.'_.
MeH1nl of snOll to fOnl ..dn, T~TO'
AutOC(lnver,lon (auregstion) ofsn""to/OTllcra",.1.
.........bllbtlc frecdllZof ...lnto f.... CI"aUJ'I01.
Accretlonofcloud"atnb)'ITaur-1.
Accretlon of cloud lee by 1T.upe1.
Accretlonofra1nbY/lraup.l.
Accretion of SnOW bY/lraupel.
Subli..U -sC
= exp (-0.022 ~ - 0.88 Tc - 3,8) liter-I, -SC ~ Tc
~ -2oe (2-26)
.. 160 liter-I, ~2OC > T
c
The initial seeding pattern for silver iodide used for the results
reported below is composed of 11 core grid points in a horizontal or
vertical pattern with the exponential decrease in the surrounding grid
~;n~~~d;:~~~b~: ~~V~ff~~lih: ~~l ~s;ciJ '~i;i~~' ab~u~o~~o V:l~~ for
AgI per kilometer in the y-direction.
As. described in Hsie et a1. (1980). the silver iodide particles
interact with the cloud liqlii~rain. and water vapor fields to produce
ice crystals. Contact and deposition nucleation are siallated directly.
tdl.ile condensation-freezing nucleation effects are i1l{l11cit in the
generator nucleation curve for the activation of AgI particles (2-26).
The physical effects of inertial i1l:pact and Brownian collection are
modeled for contact nucleation. Most of the AsI particles work 35
deposition or condeMadon freedng nuclei in the IlOdel.
li'ith regard to the AsI activation. the modeled activation rates
have been found to be too high in the warner portions of the cloud
(-S·C to -20·C). particularly if the AgI particles rell8in in the war.
sectors of the cloud for long periods of time (private connunieations
with B. A. Silvennan). The problem relates to the continual activation
of the AgI particles $0 that (2-26). while properly representing the
;~~~~:~e:c~}V~~;O~~fp~~~i~;;:~;; ~:a~t~~ :~C~~:i::me~~=:r:~~~
[see Eq. (27) and prior discussions in Hsie et 81. (1l180)]. This
problem is less serious for strong updraft cloUdS than for weak up­draft
clouds because these more vigorous clouds will quicklY carry
the seeding agent into colder regions where, in any event, all of
the AgI particles ...·ould be activated.
The interpretation one should place on the AgI seeding effects on
the stratus-type clouds reported on below is to consider that JIlUch more
silver iodide than modeled would be required to provide the indicated
effect in a field experiment. Alternatively, the amount of CO2 required
to produce the equivalent number of ice crystals as the AgI could be
calculated, but even here problems arise because of the short time that
the C02 produces crystals in the cloud. So the combination of time of
fOTlll8tion and nwnber of ice crystals formed is difficult to produce the
same effect in both AgI and C02 seeding simulations. This is as yet an
unresolved problem in the modeling ot seeding effects in this cloud
model. Coordinated modeling and field efforts will be required to
sort out the many complexities. The cloud model seeding results to
follow are suggestive and not definitive.
15
16
3. FIELD OBSERVATIONS AND CLOUD MODEL RESULTS,
19 FEBRUARY 1980 CASE
3.1 Observations
The radiosonde sounding for this case is given in Fig. 3. The
marked stability and high moisture content in the lower layer lias
overlain by an unstable, dry level aloft. As described in PEP Report
No. 22, a cold low, developing from a lagging surface trough, deepened
west of Portugal and remained south of the project area for the period
18-20 February. On the 19th, the upper cloud layers thickened during
the morning hours. A NW-SE oriented rain band moved through the area
from SW to NE during midday. Cloud physics ain:raft flights reported
the core of the band to be completely glaciated and precipitating,
while the southwest rear portion was layered with ice and liqUid,
coexisting but not precipitating. Echo tops to -40"C or colder
lowered to -lOC to -ZOC in the later stages (from> 8 hrs to 5 hrs
or less). At the time of the lowering, the uniform echo bec8llle more
"spotty," indicative of convective activity. The discussion indicates
formation of precipitation at higher levels (7 km MSL) and advection
to regions downwind (NE) of its origin.
The model results cannot hope to mimic all of the details of this
development, particularly in light of the lack of information about
the mesoscale convergence/divergence fields that may have been
influencing the precipitation develOplltent. Application of the model
to this sounding is made to see what kind of precipitation developtnent
occurs. Convergence is superimposed in the lower levels, divergence
aloft to capture the essence of the formation of any type of stratified
cloud. The presence of the upper low would appear to justify this use
of convergence, but the proper magnitude to use is not known. Also,
the variation of the real cloud tops with time during the 19th would
indicate a diminuation of the convergence after the deeper cloud layers
had developed, which ,,·as not done in the model runs indicated below.
In hindsight, the model is probably capturing the beginning stages of
a system and not the end or more mature stages as observed.
3.2 Model Results - Unseeded Cloud
The natural case (Fig. 4) is characterized by a fairly uniform
stratus deck for the early stage of the simulation (first 30 min).
The vertical n:otion is very weak « 1 m s-l) and shows little organi­zation
during this period. Cloud water contents are also quite low,
generally less than 1 g kg- 1 (0.5 g m- 3). The stratus deck deepens
very gradually with time during the initial 30-min period. Shortly
after the first cloud ice (ice crystals) develops (at -20"C and
shortly before 15 min), the snowfield is in1 tiated, but 1t also
develops very slowly. After about IS min of additional growth of
the snowfield, small turrets become evident near cloud top and are
associated with the development of the snow. These turrets are the
£.!E.:...l: Skew-T plot of 19 February 1980 sounding taken at Villanubla.
Spain. at 1100 G1T. Solid line is temperature; dashed line is dew
point temperature.
17
18
VAL1N2
l~ - - - - - - - - .. - - . -
, .. - - - - .... - .. - . -
: ::: - - - 30
~~ a~eO~~~~;~~~:l~:~~~eV~~~~2c~~t;~~ ~~.i~~~C;~e~i~~lU:eg:~:~:;S
~~~ng°k~~f) ~g~~. c~~~ ~~~t~~~t~~tP(~i~S~e~~~:~a~:~U~:l~~:a~~~a;~:nthan
0.1 g kg~l). The strellJlllines are dashed and indicate a speed of 5 II sec-1
when spaced 1 b apart. The solid lines are cloud outlines where the
R.H. is 100\. The nUllbers in the corner indicate the simulated real
tae and those on the ordinate are height in kll above ground.
_jar convective elell::enu of the sblUlation and inc-Tease in intensity
for a period of time with Il8Xh:UllI updrafts on the order of 10 II 5- 1.
These eleJllents eventually reach the 9 ka MiL level, while the IUin
clotxl deck top is aro\llld 6 k. AGL. Rainfall at the surface is pri­_
Tily due to the melting of snow, although the later portion of the
sillUlation indicates thllt graupel is also fOnled. (The graupel £01'118.
tion processes in the model were inhibited for all cl\Ses with the
19 February 1980 sounding by turning off the aggregation of snov to
fom graupel and by IDllUng the snmoirain interaction production more
restrictive by requiring rain or snow contents greater than 1 g kg-I
instead of 0.1 g kg-I as in Lin et al., 1983.) A radar bright band
forms during the early stages o£"""therainout. Surface accuwllltion
of rain begins during the latter part of tne first nour of simulated
time; I.S to 2.0 IIllIl of rain have accumulated on tho ground at 120 min.
In addition, results are shown for VALINS (Fig. 5), an unseeded
case with time steps identical to the dry-ice seeded cases, (The
simulation of dry ice seeding introduces the fall speed of the ice
pellets which reduces the she of the time step in the model.) The
differences in the results of these two unseeded cases indicate a
slightly enhanced and earlier precipitation process in the smaller
time-step case (VALINS). This may be due to the formation of natural
cloud ice in the model. A te1'1ll in the numerical code concerning the
depositional growth of the ice was found to initiate ice erroneously
at a rate dependent on the nUllber of tire steps, The code has subse­quently
been corrected, but all cases have not been reron since the
IIl8in character of the solution has been maintained. Nevertheless.
the c~arison of CO2 case results ....ith cOlllpatible tiEe steps rests
on fi:mer ground than the AgI cases ",'hich had different time step
intervals and a different total number of tble steps.
3.3 Dry Ice seeding SiDulations
There were three siD.1lations of dry ice seeding 1ll8de on the
19 Februaxy 1980 sounding. Dry ice seeding is siDl.llated by releasing
8 packet of CO2 pellets at a specific location and tille into the sillU­ladon.
The dry ice falls out of the cloud, but results in the pro­duction
of a slll811 amount of cloud ice in the relatively warm region
(-4 to -ISOC).
"
Cases VALICI and VALlC2 were run with the traditional (Fukuta et
~ 1971) value for dry ice effectiveness of 1011 ice crystals per­gram
of C02 sublimed in the cold region of the cloud, Case VALlCS
assumes a greater activity for C02 based on recent laboratory evidence
which suggests that C02 produces 1013 ice crystals per gram of sublimed
materinl within the supercooled portions of the cloud (Bernie Silverman,
priVAte comnunication).
20
:....m~..;...
; . ~
~: The no~seed simulation VAL INS at 30, 60, and 90 min. Syllbols
iiid"lTnes are as explained in Fig. 4.
3.3.1 VALIC} case
In the first. si'/tllJation. dry ice ~.s release ~ "'0' . .. :..;.........:. -.-:.-=" ==.-, . ' •.•.•.•.•.•.•.•. ' .•.,4 .•.•.•••.•.•.•.•.
o SEED ..:.: ::.:.:'~l,,~~~.~.:.~,~:,;.~:.~·.;:::-..-~' .:,~,,~ .
1D················ ill ...................~.
:::::::::::::::::::::::~:
J .•.•.•.•.•.•.•.•.•.•.•.•.•...•...•..•.•..•.•.• _ •••••••••••.• - . 1 •.•.•.•.•.•.•.•.•.•.•.•.• _._ •.•.•.•.•.
: ~O·SE~D·;:.:}~~,~,i~~;.,,:~~;. ~~:~:i:.:,~: .~,~j: ... [ J .:::.:.:.:.:.:::::~.
:::::::::::::::::~:~~:~::: '= . ..................... - .
~ ~~~D:; :,~:..:,,:i:;.~~;: :',,:i:.:'.:.2:~: ..:.:.:,~.i: ·1' .,.,_ ..•.'...." ...,_. '.''''-
~ t;~O~~~:) (~~~:;~s~~:m::iw:~~ ~~~wn~~~~:~tsi;:~~tion
VALINS and the seed simulation VALleZ at IS IIlin. The dashed
circles outline the seeding agent field at 12, 13, and 14 min.
:~ ::: .~. :.:. ;C:;'.:7:T0
:::: .. : jO .
1 •••••••••••••••••••
:~·:.:.~.L~
·f·····~ :WJL~~
:·~E.~.~·:~·..·~..·~.·~.·~·:·2·?·S·~~~'
) ::::::::::.:':.:::;:::::~:::~:: .,,: ..~.
l~•••••••••••••.
:-_~:~ ..._.....:..:.-~..._." _. ::..:':-_." .. •...............~. .. , ..... ,., ,.,.! .•. , .•.•.....•.•.•.•. :::::::::::::: :". ::: ::.::.:::.::;;~::: == {r .• \~ ::::::::::::::: ~ :::::': :: :',; :.:: :': :.. :.:: :
, .
oEE ~.~ ,~.~.;,~~~_;;,~~~ .. :~:,:~';.:~:n· ..·:~.~. i
!!.&.:2: Cloud icc (top two frUles) and snow content field
(bottom two frUles) cOllparisons between the no-seed siEUla­tion
VAUNS and the seed silllUlation VALIC2 at 24 -.in.
"
24
By 30 min (Fig. 8), the snow patterns are still different, aupented
8UIUJlU showing up in the regions 13 to 16 bI in from the left boundary.
The rain pattern is aho broadened and intensified by the cloud seeding
(upper panels of Fig. 8). The rain accWDUlation (Fig. 9) at 48.0 IBin
shows the additional rain was a large percentage change, but 5111811 in
absolute lUIlOunt.
3.3.3 VALleS case
A third CO2 silllUlation was run with about 8S g km- ll of dry ice
released near cloud top (T. -21°C) at 33 min into the run. Again the
location was such as to mimic an aircraft pass, but at a later time
when the cloud tops were higher and colder. More of the dry ice (32\)
is subli.ed. snow foms and depletes the cloud water. Pndpitation
changes in this case are very siJllilar to the previous case.
3.4 Silver Iodide seeding SiDJlations
A total of six silver iodide seeding siJllUlations were conducted
using the 19 februa%Y 1980 sounding as input to the numerical 'IlOdel.
The AgI is again assumed to have been released by an aircraft, usually
near _10°C at a specified amount. The AgI has no faU velocity as do
the CO2 pellets, hence it advects and diffuses along the flow field
and interacts with the supercooled cloud fields. A discussion of five
of the six simulations follows. The first case (VALIAl) was a trial
run with the seeding II\8terial placed in a location too near the right
boundary and is not discussed further.
3.4.1 VALIA2 case
the _~f~~:~e~~ ;~: fe~·~t~:e:O~nm:~e~;a~~~re~:I::::1n:t
JDaterial W85 released at this location and at this tillle to exatline the
effeets of the seeding in natural snow and cloud ice conditions. At
the release point, there was about 0.05 g kg-1 of snow which increased
in 3 1IIin to 0.1 g kg-I. This represents a few ice particles per liter
of air. Thus, the results are applicable to a cloud in its early
stages of precipitation formation. This appears to be an excessive
llllJOunt of AgI, particularly considering the lilllited area (voIUllle) over
which it was spread. This case is quite interesting, however, in that
it appears to result in a dynamic response to seeding. The cloud ice
produced frOlll JIlOst of the activated seeding material is highly localized
(see Fig. 10). As this converts to snow, the cloud water is completely
depleted in the local source region and in the immediate downstream
vicini ty. This depletion becomes evident about 6 min after seeding
(39 min). An organized updraft begins its develop1llent about 3 min
later. The updraft intensifies rather slowly at first, and then more
explosively about IS min after the seeding lIIaterial is released. This
Jl8jor convective ele_ent, evident at 60 .In, has a strong influence on
the main cloud deck for IlUch of the siDLlated period. The mui1rUlIl
~ ~
) :::::::::::::::::::::::::::::::::::::.
.':::·::::::::o:: "~
.0000<>
.00004
.00002
I
II \
,
I
,
I
1/
I
I
o
o
DISTANCE FRO" L.EFT BOUNDARY 11011
~: Rain 8ccUlllUlation at the ground (em) along the xpaxis at 48 min.
'5OII(]line is the amount from the C02 seeded simulation; the dashed
curve is that of the nopseed simulation.
(,
27
Fig. 10: The A&I seed silWlation VALIA2 at 39, 60, and 90 min. Seeding
IIaterial is contoured in th.e bottOlll frllJlle.
28
cloud top for this element is about 10 kIn AGL. As this element moves
to the right and separates from the main cloud deck. it induces a second
major convective element on the left side of the domain. Although this
element does not attain the same cloud top or intensity as the seeded
element, it, too. is quite important to overall precipitation development.
The first rain at cloud base for the silver iodide seeded case occurs
about 12 min sooner than the natural case. and the location has also
been shifted. Graupel famadon occurs at about the sallie time and
location as in the natural case. but less graupel reaches the surface
for the silver iodide case. Total accUllluiation of precipitation is
increased more markedly in this case than for the dry ice cases. Peak
values are increased about 50% and the overall domain value increased
about 20\. The precipitation has also been redistributed considerably
at the surface, although only a few points receive less precipitation.
3.4.2 VALlAS case
This case (Fig. 11) was run with 31.9 g km- l of seeding material,
a factor of 10 less than the previous case. The material was released
at the same location and at 32 min into the siJll.1lation. Again a response
to the seeding is dynamic growth, however, not quite as vigorous as in
the previous case (VALlA2). The depletion of the cloud water is delayed
by 7 min, and the convective element is reduced in size and strength when
compared to VALIA2 results at 60 mn. Both rain and graupel accUlllula- ')
tions at the surface are about 5% less throughout the simulation of
the run, with precipitation starting 5 min later in this run.
3.4.3 VALIA4 and VALlAS cases
These two cases were each run with high mounts of AgI particles
(319 g km- l ) but at later times. VALIA4 was seeded at 42 min and VALlAS
was seeded at 48 min, both at the same location as VALIA2 and VALIA3.
At 5 min after seeding, both cases had seeding effects which again
showed a depletion of cloud water. At 8 min after seeding, the stream~
lines (airflow) in both cases showed a hint of upward motion in the
vicinity of the seeding material that eventually leads to turret growth
and earlier (than the natural case) precipitation on the ground. The
total amount of rain is similar to that of VALlA2 in both cases;
however, the amount of graupel is 25% more for VALIA4.
3.4.4 VALIA6 case
The last seeding siuulation (Fig. 12) was an attempt at modeling
the release of AgI from a pyrotechnic device delivered by an aircraft.
The trail of seeding material is oriented vertically at the same loca~
tion as in the previous cases and at the heavy rate (300 g bll-l ). The
AgI particles were "dropped" at 42 min, the same as that of VALIA4, and
resulted in a very similar simulation to that of VALlA4. The total
precipitation production at 120 min was about 4% less than that in
VALIA4.
2.
Fig. 11: The AgI seed simulation VALlA3 at 45, 60, and 90 min. Seeding
lIatena} is contoured in the bottom frUle.
'" -f -. -"~~ s
~~ ~IH~ ~~T~~ ~;T;~ ~lHssit~; ;~t~~ s~t~ss~t~~ ss-s·~
sssssslDtsssssssssssssssssssssssssssssssssssss
sss'S""S'"s SSS'5~SSS,!;TSSSS-S'S'S'S-S·!t'SS-S""S".(;'Si.5~~.S
3 55SSSS A. SSSSSSSSS5SS$SSSSSSSSSSSSSS$SS$SSSSSS
5SS$SS II>' $5$55$SS$SSSSSSSSSSSSSSSSSSSSSSSSSSSS .. _.. _.. ----·-··.··----··.··.··-··-·····-··-·$055'.4·$
~: The AgI seed simulation VALIA6 at 43, 60, Bnd 90 min. Seeding
lllaterial is contoured in the bottom frame.
31
3.S~
The lack of a significant response in CO2 seeded siDl.llations for
19 February 1980 is intriguing, especially for case VALle3 which should
have produced ice crystal concentrations somewhere between those values
produced in VALlA2 and VALlAS. These results are suspect and 1Ilay be
plagued by some erroneous physical assumptions. The results are. how­ever.
consistent with earlier results for HIPLEX cases••s well as
observations which show little seeding effect if the ice processes are
already active. Another possible e.xplanation of the lack of dynode
response lIIight be related to the much shorter time period over
which the ~ exerts a direct effect cOIIPared to the Ail particles.
Additional siDulations and study are required to resolve this.
The dynamic effects induced by the silver iodide seeding are
apparently the result of the fact that the amount of latent heat of
fusion being released is lIluch more significant in terms of the overall
energetics of the cloud than what is nomally the case in pure con~
vecdve situations with much stronger updrafts. The differences in
heating and cooling due to latent heat of vaporitation associated with
the cOlllplete drying up of the cloud and resultant subsaturated localized
conditions JPUSt also be very important. These stable type clouds with
relatively low water contents thus appear to be Iklre UlC:nable to dynamic
seeding than some convective clouds. It should be noted that :much of
the latent heat release is of an indiTect or secondary nature requiring
the presence of precipitating ice~es. and is not created directly
by the seeding induced direct freedng of the cloud liquid. The lIIfIin
difference here cOlllJlare'd"'tO"earlier attempts at dynamic seeding with
the cloud Illodel appears to be related to the fact that advection is
qui te uniform compared to the much stronger nonlinear character of
the HIPLEX and Florida cases. which have been tested in the model.
The total aJJIOunt of precipitation. both rain and graupel. is shown
in Table 2 for the unseeded case and the seeded cases. The heavy
seeding case (VALIA2) results in 20\ JIOre precipitation on the ground.
The 32 g kr1 seeding rate case also produces cloud stilrolation and
dynllJllic growth. It produces 14\ JIlOre precipitation on the ground with
most of the increase coming through graupel fallout. The natural as
well as seeded cases developed graupel in the later stages due to
the interaction of rainwater and cloud ice near the o·e level. The
convection also aids in causing this graupel fonnation.
Both the natural cloud case and the seeded cloud cRses produce
large convective cells during the latter part of the silllUlations. It
is important to note. though. that the seeded cloud cells have their
roots fairly low In the stratus cloud deck. whereas the natural cloud
cells are DlOre nucerous aloft, not as well organiZed as the seeded
cells. and are smaller in breadth. They do not have as IIJCh
influence on the lower cloud deck as do the seeded cells.
32
TABLE 2
Precipitation Resul ts ~ Stratus Clouds
[
SUll differences noted Within]
30 ain of seed tiM
SEEDING
CASE TIME "(iTn) r."t"m""'""')
CO,
VAUNS No Seed
VALleZ 12
VALIC! 33
35.6
PRECIPITATION
14.1 49.7
".
ALlN2 NatUl'al 39.1 12.1 51.2
ALl'" 33 31. 40.3 21.1 61.4
ALIA:! 32 31.9 39.3 19.3 58.6
ALiA4 42 31. 41.9 25.5 67.4
ALlA3 48 31. 39.9 19.7 59.6
ALIA" 42 300 40.7 23.7 64.4
L
EXMlination of tho model's water vapor field shows that nearly
1 g kg~l of water can be condensed for a 1 km rise. The mesoscale
motions caused by convergence are of the order of ..agnitude 10 em s-l •
This bplies periods exceeding two hours to condense 1 gil of water.
The motions set off by the cloud seeding are of the order _ s-I and
tapIr 10's of IIlin for the condensation of significant water lUIlOUnts.
Consequently, the whole condensation/precipitation process h speeded
up by an order of mAgnitude or lIIOre by the seeding.
The enhanced motion in this stTat~ case was aided by the upper
layer instability. The seeded region was able to tap the instability
in the unstable region more effectiVely than the unseeded clouds and
grow vigorously. Even with no upper layer unstable regions, the
enhanced JIlOtion in the lower stable region appeared capable of
speeding up the cloud life histories and affecting a redistribution
as well as an increase in precipitation. However, lllOdel :runs with
IIIOTe appropriate soundings will be needed to test this last point.
The lD:XIel results also focus attention on the part _esoscale
convergence plays in developing the clouds. Presumably, the conver­gence
values are not constant but are an evolving phenomena within the
target area. Each frontal and trough passage probably induces such
responses.
A full description of the effects of seeding of stratus type
clouds over the entire basin area would probably require 8 1'esoscale
IlOdel with a cloud scale model superimposed. At the present. tille,
such mdels are under developll:ent, but pTObably will not be available
for any planned experiments within the next few years. In the future,
they should prove very helpful for the assessment of modification
potential of such systeDtS.
33
34
4. FIELD OBSERVATIONS AND CLOUD M:lDEL RESULTS,
14 MAY 1981 CASE
4.1 Introductory Remarks
The work that has been done on the 14 May 1981 case is incomplete.
The sounding for 0700Z was the only atmospheric sounding made available
to us initially. so the initial runs were made with this sounding. Not
until much later was it realized that the aircraft data and other
observations were taken nearer the llOaZ sounding data. A few runs
have been made with this later sounding. This timing difference causes
Il\8.ny changes in the numerical results because the synoptic condition
was changing rapidly throughout the morning hours, as described below.
Consequently, the seeding results are available only on model clouds
typical of the 0700Z sounding, which produced clouds deeper and lllOre
active than those produced later in the day. The comparison of model
clouds produced using the 0700Z and 1100Z soundings shows the effects
of sounding and convergence differences on the model results.
4.2~
The aircraft flight S1JllWaries and synoptic data on file at the
WHO indicate that there was a weak upper level 101., ..
2. " , .• {j. •.•.• • .•.•. , ':::: .. : ' :::::::::: - .. ::::' ;7'
o ,.._._ ..._ "':,..;.:~~:..". ':.:=...:..,~:"'_"" '.'''_
~: The cloud water field of VAL2NS at 75, 81. 87, and 93 min,
tlilit'COntouring interval changes at 93 min; units are in g g~l.
Note
,..__ -_...._....-_.......~if= ~.., ,., . J •••• • ".n .•.•. '...... . < :,::.': ... ::. : :,::: :,::::.(BQ::..:.
1 ,,:::::. :... .:'.: ::: ::: ::::: :' ., ." •
o , _,- __' ,, , " .._ ' ... ".._.....•." ..,,_ ...
r. ····] ......................................
::::::::..:::~:::::::~ , ~ ................. .. .. . 2 •.•••••••••••••••••••••••••••••••••• , ::::::::::::::::,'0:":::::::::::::'"
o ' '_:.....:.. .. ',_.~,':,~~~,~~,_'.:~.:._:_l., .',•..:
j:~&. ll; The hail content field of VAL2NS at 81, 87, and 93 min. Note
t at t e contouring interval changes fOT each frame and that the scale
factor changes at 93 minj units are In g g_l.
..~ .... ....... - . - .
.:~ ~ :::::~ ~'~ ~ :~ ~ ~ ~ .~ ;:::~ :::;~i~ ~ ~ :~ ~ :~ : , ::.. . . . .:~ -_ -. ::. . , . ' .,.,__'_-,,_ _,.._. , .
.~...................................... , -.- . .= . ............... -.- .
J .•.•.•...•.•.•.••.•...•.••••••••••••••.•.•.•.• . 1 ..•.••••• , •.• _ .•.•.•• _ .•.• _.
:; :.:: ~.~·..:~~~~~-:~·.M:.~;:~:~:.:~~: ';
1..·.·.·.·.·.·.·.·.·.·.·.·.·.·.·.·.] 5 •••••••••••••••••• . : :: :::::::::::::::
J'. .•.••••••••••••••••. J .•.•.••.•.••••••••••••• ~~ . ' ... ···~·······81
o < ._ ..,_ .,,,_,_ ,__ ,,,__....~"'....,._ ' ...
FgS. If The rain content field of V~L2NS at 81, 87, and 93 min. Note
t at t e contouring interval changes at 93 Idn and the scale factor
changes at 87 IIlinj unit" are in g g_1.
41
42
At least five cells can be identified in the cloud water content fields
at the earlier times (Fig. 15, 7S min). The cloud top extends to over
5 km (AGL) or 5.9 km (MSL), which is too deep compared with the obser­vations
later in the day. This 15 caused by the model convergence
(5 x 10- 5 5-1) and the moist 0700Z sounding used for the initial
conditions.
These cells evolve in a realistic fashion. The snow content
(Fig. 16) is the first precipitation field to form, followed by
graupel/hail (Fig. 17) and then rain (Fig. 18) in the lower eleva­tions.
Only a few mm of rain and,graupel accumulate on the ground
after 30 min of cell development (63-93 min).
4.4 Model Results - Seeded Cloud (0700Z Sounding)
Figures 19 through 23 show the seeded case results. The cell
centered about 6 km from the left boundary in Fig. 14a is seeded with
241 g of C02 (per km in the unmodeled y-direction) at 66 min. The
seeding material is initiated in the model at about .3 km height (at
about -lO·C) in a box pattem, as described above (Sec. 2.3.1). The
CO2 forms cloud ice which interacts with the supercooled cloud liquid
to form snow and then graupel. The seeded cell forms precipitation
about 6 min earlier than its unseeded counterpart.
At 7S IDin. the depletion of the cloud water (Fig. 20) by the snow
and graupel is quite evident in the seeded cell compared to the unseeded
cells. By 81 min in the unseeded case (Fig. 15), the "seeded cell
counterpart" has depleted the liquid water also, because of the natural
precipitation processes, primarily accretion of liquid water by snow
and graupel.
A light rain shower is depicted at 81 min in the seeded case at
about 11 km in from the left boundary (Fig. 19). The graupel field in
Fig. 22 and rain in Fig. 23 show that the shower from the seeded cell
is over by 93 min. A similar, but lighter, shower shows up in the
unseeded case at 87 min (Fig. 14t) , which also ends by 93 min
(Figs. 17 and 18).
4.5 Seeding Potential
4.5.1 Method
Using the 07002 Va11anubla sounding, the aircraft (AlC) data from
1100 to 1330, and the radar data from 1100 to about 1400 combined with
numerical model results allow estimates to be made of the seeding
potential on this day and to be compared with the radar and aircraft
methods of estimation.
Fig. 19a: The CO2 seed sbllUlation VAL2el at 75, 81, and 87 min. Symbols
and hnes are as explained in Fig. 4.
"
Fi~. 19b: The CO2 seed simulation VAL2el at 93 and 99 min. Symbols
an hnes are as explained in Fig. 4.
.~ .-............... . .....•.•.
:::~~
J a·.... ." .•."..... .......
2 : .' : ".::::'" •• : ••••
: '::::.,' .•or;;: ~:::::::::. ~::::';1' -,_ _.",__.-..'_.,._- _._.. ...
, '_..,' .(".,......_. ,-, _.•, ' ... -.., " _...
.~.~=::::::.:..:.:.'::::::.:.:.:.:.:.::::::::: s::::::::::::: .
. . .. . ,. . .. .,.. ". ...n." .
l • " ••_~. • .
> :. ' • ", ., •• ::. • - ';::. ; :::.~ o:.'::::.:.·~;
, _ ..._.-_0.__" ,.._. _ ...
~: The cloud water field of VAL2e} at 75, 81, 87, and 93 Din.
~.t contouring interval changes at 93 min; tmits are in g g_1,
4S
46
___ .•.1 _ ,_,,_ 0._"''''''''' ._.....
..., _•. , " '.1"''''
1.·'..·1·-1·T-I·~·• ·•·••·••·•·•.•·••·.•·..•···.·. •·.•]·.•. .' ......... . ~, .
:::::::::::::~::::::::::::::::::
:::,::, :iL~~,~.~: :!•.~.~i: ~..:..;.:~:~~u:,..:.:,~j: ~~ . ..., ' " , ..
Fig. 21: The snow content field of VAL2el at 75, 81, 87, and 93 lIlin.
NOte't1i'at the contouring interval changes at 93 min; units are in g g-l.
47 ·1Ii·tJi ..... - ,.,. . . ~ . .
.==.. =. :!.l.>~:'~ fhTy~.
o ,_,_ -4.'_....,':',:.;~~_~,~:',.;.....,~_;.., 0_ AssUlJl.ing thn this difference applies to all
the cells (all cells being seeded ill an ideal experilllellt). then the
extra rain averaged over the ent! re are~ (8\ of t.he tot.a) area is
covered by radar echoes) over a 3-hr period is
t.R2 " 1I~ TF/T (Fraction of Area)
::: 0.20 lllD'l • 6 • 0.08
• 0.096 :: 9.6 x 10-2 ...
The total change of precipitation i5 the 5U11 of the two. IC'hich is
(4.5)
The radar RVIA analysis for this case in PEP Report '28 yields
an increase of 47 x 10-2 1IIIl (frOlll a 0.158 _ hr-1 increase in areal
averaged rain rate for a 3-hr period).
52
4.5.4 Discussion
This preliainary exercise has indicated how one lIIight use one,
two. or three-di.ensional cloud model results combined with aircraft
and radar observations to estilll8te the seeding potential of a region
during. particular day. For an extrapolation to seasonal results,
IllOre case study days should be analyt.ed and an average effect deter­mined
for the characterisdc clouds in the reglon -- the Mi. AC. C,
and B type clouds. Probably, at least 5 to 10 days would be needed
for each type of cloud.
The results shown here use a 2-D, tiEe-dependent cloud model.
but the possible use of I-D or 3-D, time--dependent cloud models would
follow the same procedures. but using more or fewer assumptions, as
appropriate, about cloud coverage. nUllber of cells, etc.
Table 3 gives a summary of the model, Ale and radar RVIA results.
4.6 Model Res~lts - Unseeded Cloud 1l00Z Sounding
Figures 24-27 show the numerical results for this case. Figure 24
depicts the cloud outline 30~66 min after model start up. The symbols
Sand· represent snow and rain contents greater than 0.1 g kg~l.
respectively; the stre8ll function is given by the dashed lines at
inten'als of 5 x 103 kg m~2 s-l. This model run was initiated
with the lWOZ, 14 May 1983 sounding with heating and evaporation
rates at the earth's surface approxiJaating those for the site.
Saall clouds topping out at about 2.0 to 2.6 bl (AGL) (station
height is about 850 m) are present at 30 mn. which grow eventually
to more than 4 kill by 66 mn. A s1liall cloud 11 klII in from the left
boundu)' grows to only 2.5 bt and then dissipates, foming negligible
precipitation. The taller clouds produce over 1.0 DII of peal:. accumu~
lated precipitation by 60 mn. Cloud bases range frawl 0.4 to 1.4 D.
about 0.4 Ul lower than the obsen'ed clouds indicating IllOre water
vapor in the model atmosphere than in nature on this day.
Figures 25-27 show the cloud water. snow. and. graupel/hail
contents. Values of 1 to 2 g kgp1 occur in the cloud water and a
few tenths of a g kg-1 in the snow and hail contents.
Figure 28 gives instantaneous cross sections of snow. graupel,
and cloud water through the central cloudy region at various model
tiJlles. 42 min - 63 min, and at heights corresponding to the level at
which the Queen Air aircraft flew. Comparison of this figure with
Fig. 29 taken from the real data (and is a time cross section, but
with I IlIin "4 0) shows the IOOdel disturbances to be of the saJlle
scale as those in nature. but to have too large cloud liquid water
contents (even after allowance is made for the IllOdel values in
g kg-1 to be converted to g m- ~. Also, the change of cloud water
53
TABLE 3
Sta:I&ry of Results·
llR Aircraft (AlC)
R Iok>del Results.
(NC) Technique
PRECIPITATION (Areal Averaged)
(Uni ts 10-2 DIll)
(30-1I1n cycle) (36-1110 cYcle)
1.4
4.7
EQlJATION
(4-3)
llRl Model Resul ts
R2. Model Results.
Radar Technique
R2. Radar CRVIA)
4.3
9.'
47.0
13.9
12.0
10.8
22.8
(4_4)
(4-5)
-- PEP 28
(4_4) & (4-5)
~bserved Areal
Averaged Precip.
__________ 13 _
!Model Precipitation 14.9 22.0 (4_S)t
Results I
·See text for explanation of entries. .
t (4-5). but with unseeded average precipitation replacing ARo. I
the difference in precipitation between seeded and unseeded cells. I
54
1i:··:····~····2····:·· 5-:~
."" '''''''''''''' " ,,,,;12
Fig. 248: The natural simulation of VAL3N2 at 30, 36, 42, and 48 min.
Symbols and lines are as explained in Fig. 4.
55
Fi5" 24b: The natural simulAtion of VAL3N2 at 54. 60. and 66 adn. Symbols
an hnes are as explained in Fig. 4.
56
,..' '_ .•. _ .,,, . 0>, , ,,,, _.0>, ,, •.,,..,,.•. _ .... ,., ,."" ",_ .." ..."
~ig. 2~a: The cloud water field of VAL3N2 at 30, 36. 42. and 48 JDin.
ate t at the contouring interval changes at 36 min; units are in g g~l.
57
, - '••_ ._,., , ..' q _ " _ .. -.._ , ..
._ _' .._..•,._ _ _- _ ...
,.._._., _ .,_ _ , _ .., " , 0.'_- , ..
Fig. 2Sb: The cloud water field of VAL3N2 at 54, 60, and"66 .dn. Note
that the contouring interval changes at 60 min; units are'in g g-1.
58
'_'_'0.'_"''' .."_'"" ""' ", , ' ... ,_."."••, __
",.J ,..' '_ ,_..,,, .,., """_,." '."".., ,.."." _",
F~. 2~a: The snow content field of VAL3N2 at 36, 42, and 48 rain. Note
t at t e contouring interval changes at 42 and 48 min, and that the scale
factor changes at 42 and 48 min; units are in g g_l.
a
........-.•._ ._,..__.-_- -_. __ _ _... '.'--
:E~~~
,_,__._..... 0..___...-._."_M_._...•• __... " .." .... ..__
FiG' 26b: The snow cont.ent. field of VAL3N2 at 54, 60, and 66 min;
unltS are in g g-l.
"
60
, _ .."..,...•,,, •."'"0"0.0..0..._..-", .." ,_,,,,,.,.,..,, ""',,,..,••. '.'_'"
'••.._......."...,.......,.......""-",, ,,._._..""."""""" '.'_'"
Fix. 27: The graupel/hail content field of VAL3N2 at 54. 60, and
66 min; units are in g gpl.
o
42 MIN
(1320-1323) SNol.. 45 MIN . GRAUPEL. ,,,g1-'] /\
j '\~
48 MIN
(1325-1328)
51 MIN
SNOW .. . GRAUPEL.
[gkg-']
54 MIN
(1331-1335)
• LWC i\ . -+--[~.~gk~'1 - f- JUV\ ,/\ j\. j',f{\
o 35191113 351911130 3 5 1 ~ 11 13 3 5 7 9 11 13 11 9 7 5 3
~, Model output of ~n(l'll1 a pot.ent.ial for
dynamic effects in a nearly :-oist adiabatic. at:llosphere which produces
prl1lltlrily stratifora clouds. This is an effeet not previously con­sidered
for such clouds and needs further modeling and field verifi­cation.
If the theory is supported. the seeding of stratified clouds
could take on increased importance. because the signal is so clear
and should be easily detected in field experaents. The statistical
and physical tests should be able to give significant answers in a
relatively short time.
More needs to be done in the studies of both C- and A-type cloud
5ystelllS. The seeding siDlulations on convective clouds are very
incomplete. Investigations of how the cloud seedin& works on clouds
with some natural ice are necessary. The relative illlportance of the
Ilicrophysical and dynamical effects of the seeding should be detect~
able in cloud seeding simulations (Orville and Chen, 1982) and should
help in understanding the cloud seeding effects.
Further applications of these results to the PEP data set are
possible. The nUllber of days with lIIOist adiabatic conditions in a
particular season could be detennined and the seeding potential for
that type of cloud estilllAted. After further slllJJlations are done
on C~type cloud days, mre quantitative predictions could be made
of the seeding potential for such days.
Whether or not further studies are done on this data set,
significant results have been produced. New insights have been
gained regarding cloud seeding effects. The work with models and
observations is an ~runt start and shows a new way of obtaining
estimates of cloud seeding potential.
.5
ACKNOWLEDOONT
Acknowledplent is made to the World Meteorological Organi:r.ation
and to the National Science Foundation under Grant Nos. ATM-7916147 and
,,'1)1.8311711 for funding this effort.
We acknowledge Fred Kopp's fine work in doveloping the dry ice
seeding silllUlations used in this study. We thank Mrs. Jote Robinson
for her excellent assistance in report preparation and typing.
AcknowledgJDent is made to the National Center for AtllOspheric
Research, which is sponsored by the National Science Foundation, for
the computer time used in this research.
66
6. REFEREn:ES
Berry, E. X., 1968: Modification of the "ana rain process. Proe. 1st
Nat!. Con!. We•• Modif•• Albany. Amer. MetC 342-350.
smith. P. L•• Jr., D. J. Musil, S. F. Weber, J. F. Spahn. G. N. Johnson,
and W. R. Sand. 1976: Raindrop and hailstone size distributions
inside hailstorms. Preprints Intn!. Conf. Cloud PhySics.
Boulder, CO. Amer. Meteor. Soc •• 252-257.
Srivastava, R. C•• 1967: A study of the effects of precipitation on
cumulus dynamics. J. Atmos. Sci., ~, 36-45.
Wiin-Nielsen. A., 1~79: On phase speed errors due to various time
differencing schemes. Numerical Methods Used in Atmospheric
Models, Vol. II, GARP Publications Series No. 17, WMO. 438~473.
Wisner. C., H. D. Orville. and C. Myers, 1972: A numerical model of
a hail-bearing cloud. J. Atmos. ScL, ~. 1160·1181.
This info1'lll8tion provided in accordance with
Executive Order No. 75-6, State of South Dakota.
Office of the Governor:
(a) Total cost per copy (preparation 6; printing)
(Pre-press estimate) ., $3.19
(b) Total no. of copies .. 400
(e) Purpose" Present research results
o
o